1
|
Shaw C, Weimer BC, Gann R, Desai PT, Shah JD. The Yin and Yang of pathogens and probiotics: interplay between Salmonella enterica sv. Typhimurium and Bifidobacterium infantis during co-infection. Front Microbiol 2024; 15:1387498. [PMID: 38812689 PMCID: PMC11133690 DOI: 10.3389/fmicb.2024.1387498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Accepted: 04/12/2024] [Indexed: 05/31/2024] Open
Abstract
Probiotic bacteria have been proposed as an alternative to antibiotics for the control of antimicrobial resistant enteric pathogens. The mechanistic details of this approach remain unclear, in part because pathogen reduction appears to be both strain and ecology dependent. Here we tested the ability of five probiotic strains, including some from common probiotic genera Lactobacillus and Bifidobacterium, to reduce binding of Salmonella enterica sv. Typhimurium to epithelial cells in vitro. Bifidobacterium longum subsp. infantis emerged as a promising strain; however, S. Typhimurium infection outcome in epithelial cells was dependent on inoculation order, with B. infantis unable to rescue host cells from preceding or concurrent infection. We further investigated the complex mechanisms underlying this interaction between B. infantis, S. Typhimurium, and epithelial cells using a multi-omics approach that included gene expression and altered metabolism via metabolomics. Incubation with B. infantis repressed apoptotic pathways and induced anti-inflammatory cascades in epithelial cells. In contrast, co-incubation with B. infantis increased in S. Typhimurium the expression of virulence factors, induced anaerobic metabolism, and repressed components of arginine metabolism as well as altering the metabolic profile. Concurrent application of the probiotic and pathogen notably generated metabolic profiles more similar to that of the probiotic alone than to the pathogen, indicating a central role for metabolism in modulating probiotic-pathogen-host interactions. Together these data imply crosstalk via small molecules between the epithelial cells, pathogen and probiotic that consistently demonstrated unique molecular mechanisms specific probiotic/pathogen the individual associations.
Collapse
Affiliation(s)
| | - Bart C. Weimer
- Department of Population Health and Reproduction, School of Veterinary Medicine, 100K Pathogen Genome Project, University of California, Davis, Davis, CA, United States
| | | | | | | |
Collapse
|
2
|
Soh M, Tay YC, Lee CS, Low A, Orban L, Jaafar Z, Seedorf H. The intestinal digesta microbiota of tropical marine fish is largely uncultured and distinct from surrounding water microbiota. NPJ Biofilms Microbiomes 2024; 10:11. [PMID: 38374184 PMCID: PMC10876542 DOI: 10.1038/s41522-024-00484-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 02/06/2024] [Indexed: 02/21/2024] Open
Abstract
Studying the gut microbes of marine fishes is an important part of conservation as many fish species are increasingly threatened by extinction. The gut microbiota of only a small fraction of the more than 32,000 known fish species has been investigated. In this study we analysed the intestinal digesta microbiota composition of more than 50 different wild fish species from tropical waters. Our results show that the fish harbour intestinal digesta microbiota that are distinct from that of the surrounding water and that location, domestication status, and host intrinsic factors are strongly associated with the microbiota composition. Furthermore, we show that the vast majority (~97%) of the fish-associated microorganisms do not have any cultured representative. Considering the impact of the microbiota on host health and physiology, these findings underpin the call to also preserve the microbiota of host species, especially those that may be exposed to habitat destruction.
Collapse
Affiliation(s)
- Melissa Soh
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, 117604, Singapore
| | - Ywee Chieh Tay
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, 117604, Singapore
| | - Co Sin Lee
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, 117604, Singapore
| | - Adrian Low
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, 117604, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, MD6-Centre for Translational Medicine, 14 Medical Drive, Singapore, 117599, Singapore
| | - Laszlo Orban
- Frontline Fish Genomics Research Group, Department of Applied Fish Biology, Institute of Aquaculture and Environmental Safety, Georgikon Campus, Hungarian University of Agriculture and Life Sciences, Keszthely, 8360, Hungary
| | - Zeehan Jaafar
- Department of Biological Sciences, National University of Singapore, Singapore, 117558, Singapore
| | - Henning Seedorf
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, 117604, Singapore.
- Department of Biological Sciences, National University of Singapore, Singapore, 117558, Singapore.
| |
Collapse
|
3
|
Kirby TO, Sapp PA, Townsend JR, Govaert M, Duysburgh C, Marzorati M, Marshall TM, Esposito R. AG1 ® Induces a Favorable Impact on Gut Microbial Structure and Functionality in the Simulator of Human Intestinal Microbial Ecosystem ® Model. Curr Issues Mol Biol 2024; 46:557-569. [PMID: 38248338 PMCID: PMC10814853 DOI: 10.3390/cimb46010036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/23/2024] Open
Abstract
Modulation of the human gut microbiome has become an area of interest in the nutraceutical space. We explored the effect of the novel foundational nutrition supplement AG1® on the composition of human microbiota in an in vitro experimental design. Employing the Simulator of Human Intestinal Microbial Ecosystem (SHIME®) model, AG1® underwent digestion, absorption, and subsequent colonic microenvironment simulation under physiologically relevant conditions in healthy human fecal inocula. Following 48 h of colonic simulation, the gut microbiota were described using shallow shotgun, whole genome sequencing. Metagenomic data were used to describe changes in community structure (alpha diversity, beta diversity, and changes in specific taxa) and community function (functional heterogeneity and changes in specific bacterial metabolic pathways). Results showed no significant change in alpha diversity, but a significant effect of treatment and donor and an interaction between the treatment and donor effect on structural heterogeneity likely stemming from the differential enrichment of eight bacterial taxa. Similar findings were observed for community functional heterogeneity likely stemming from the enrichment of 20 metabolic pathways characterized in the gene ontology term database. It is logical to conclude that an acute dose of AG1 has significant effects on gut microbial composition that may translate into favorable effects in humans.
Collapse
Affiliation(s)
- Trevor O. Kirby
- Research, Nutrition, and Innovation, Athletic Greens International, Carson City, NV 89701, USA; (P.A.S.); (J.R.T.); (T.M.M.); (R.E.)
| | - Philip A. Sapp
- Research, Nutrition, and Innovation, Athletic Greens International, Carson City, NV 89701, USA; (P.A.S.); (J.R.T.); (T.M.M.); (R.E.)
| | - Jeremy R. Townsend
- Research, Nutrition, and Innovation, Athletic Greens International, Carson City, NV 89701, USA; (P.A.S.); (J.R.T.); (T.M.M.); (R.E.)
- Health & Human Performance, Concordia University Chicago, River Forest, IL 60305, USA
| | - Marlies Govaert
- ProDigest BVBA, B-9052 Ghent, Belgium; (M.G.); (C.D.); (M.M.)
| | - Cindy Duysburgh
- ProDigest BVBA, B-9052 Ghent, Belgium; (M.G.); (C.D.); (M.M.)
| | - Massimo Marzorati
- ProDigest BVBA, B-9052 Ghent, Belgium; (M.G.); (C.D.); (M.M.)
- Center of Microbial Ecology and Technology (CMET), Ghent University, B-9000 Ghent, Belgium
| | - Tess M. Marshall
- Research, Nutrition, and Innovation, Athletic Greens International, Carson City, NV 89701, USA; (P.A.S.); (J.R.T.); (T.M.M.); (R.E.)
| | - Ralph Esposito
- Research, Nutrition, and Innovation, Athletic Greens International, Carson City, NV 89701, USA; (P.A.S.); (J.R.T.); (T.M.M.); (R.E.)
- Department of Nutrition, Food Studies, and Public Health, New York University-Steinhardt, New York, NY 10003, USA
| |
Collapse
|
4
|
Wheeler C, Pearman JK, Howarth JD, Vandergoes MJ, Holt K, Trewick SA, Li X, Thompson L, Thomson-Laing G, Picard M, Moy C, Mckay NP, Moody A, Shepherd C, van den Bos V, Steiner K, Wood SA. A paleoecological investigation of recent cyanobacterial blooms and their drivers in two contrasting lakes. HARMFUL ALGAE 2024; 131:102563. [PMID: 38212085 DOI: 10.1016/j.hal.2023.102563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 12/17/2023] [Accepted: 12/18/2023] [Indexed: 01/13/2024]
Abstract
Cyanobacterial blooms are one of the most significant threats to global water security and freshwater biodiversity. Interactions among multiple stressors, including habitat degradation, species invasions, increased nutrient runoff, and climate change, are key drivers. However, assessing the role of anthropogenic activity on the onset of cyanobacterial blooms and exploring response variation amongst lakes of varying size and depth is usually limited by lack of historical records. In the present study we applied molecular, paleolimnological (trace metal, Itrax-µ-XRF and hyperspectral scanning, chronology), paleobotanical (pollen) and historical data to reconstruct cyanobacterial abundance and community composition and anthropogenic impacts in two dune lakes over a period of up to 1200 years. Metabarcoding and droplet digital PCR results showed very low levels of picocyanobacteria present in the lakes prior to about CE 1854 (1839-1870 CE) in the smaller shallow Lake Alice and CE 1970 (1963-1875 CE) in the larger deeper Lake Wiritoa. Hereafter bloom-forming cyanobacteria were detected and increased notably in abundance post CE 1984 (1982-1985 CE) in Lake Alice and CE 1997 (1990-2007 CE) in Lake Wiritoa. Currently, the magnitude of blooms is more pronounced in Lake Wiritoa, potentially attributable to hypoxia-induced release of phosphorus from sediment, introducing an additional source of nutrients. Generalized linear modelling was used to investigate the contribution of nutrients (proxy = bacterial functions), temperature, redox conditions (Mn:Fe), and erosion (Ti:Inc) in driving the abundance of cyanobacteria (ddPCR). In Lake Alice nutrients and erosion had a statistically significant effect, while in Lake Wiritoa nutrients and redox conditions were significant.
Collapse
Affiliation(s)
- Caitlin Wheeler
- Massey University, Tennent Drive, Palmerston North 4410, Aotearoa, New Zealand
| | - John K Pearman
- Cawthron Institute, Private Bag 2 Aotearoa, Nelson 7042, New Zealand
| | - Jamie D Howarth
- School of Geography, Environment and Earth Sciences, Victoria University of Wellington, PO Box 600 Aotearoa, Wellington 6012, New Zealand
| | | | - Katherine Holt
- Massey University, Tennent Drive, Palmerston North 4410, Aotearoa, New Zealand
| | - Steven A Trewick
- Massey University, Tennent Drive, Palmerston North 4410, Aotearoa, New Zealand
| | - Xun Li
- School of Geography, Environment and Earth Sciences, Victoria University of Wellington, PO Box 600 Aotearoa, Wellington 6012, New Zealand
| | - Lucy Thompson
- Cawthron Institute, Private Bag 2 Aotearoa, Nelson 7042, New Zealand
| | | | - Mailys Picard
- Cawthron Institute, Private Bag 2 Aotearoa, Nelson 7042, New Zealand; Department of Ecology and Environmental Science, Umeå Universitet, Linnaeus väg 4-6, Umeå 907 36, Sweden
| | - Chris Moy
- Department of Geology, University of Otago, 360 Leith Street Aotearoa, North Dunedin, Dunedin 9054, New Zealand
| | - Nicholas P Mckay
- School of Earth and Sustainability, Northern Arizona University, Flagstaf, AZ, United States
| | - Adelaine Moody
- School of Geography, Environment and Earth Sciences, Victoria University of Wellington, PO Box 600 Aotearoa, Wellington 6012, New Zealand
| | - Claire Shepherd
- GNS Science, 1 Fairway Drive Aotearoa, Avalon, Lower Hutt 5011, New Zealand
| | | | - Konstanze Steiner
- Cawthron Institute, Private Bag 2 Aotearoa, Nelson 7042, New Zealand
| | - Susanna A Wood
- Massey University, Tennent Drive, Palmerston North 4410, Aotearoa, New Zealand.
| |
Collapse
|
5
|
Wilson AN, St John PC, Marin DH, Hoyt CB, Rognerud EG, Nimlos MR, Cywar RM, Rorrer NA, Shebek KM, Broadbelt LJ, Beckham GT, Crowley MF. PolyID: Artificial Intelligence for Discovering Performance-Advantaged and Sustainable Polymers. Macromolecules 2023; 56:8547-8557. [PMID: 38024155 PMCID: PMC10653284 DOI: 10.1021/acs.macromol.3c00994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 09/30/2023] [Indexed: 12/01/2023]
Abstract
A necessary transformation for a sustainable economy is the transition from fossil-derived plastics to polymers derived from biomass and waste resources. While renewable feedstocks can enhance material performance through unique chemical moieties, probing the vast material design space by experiment alone is not practically feasible. Here, we develop a machine-learning-based tool, PolyID, to reduce the design space of renewable feedstocks to enable efficient discovery of performance-advantaged, biobased polymers. PolyID is a multioutput, graph neural network specifically designed to increase accuracy and to enable quantitative structure-property relationship (QSPR) analysis for polymers. It includes a novel domain-of-validity method that was developed and applied to demonstrate how gaps in training data can be filled to improve accuracy. The model was benchmarked with both a 20% held-out subset of the original training data and 22 experimentally synthesized polymers. A mean absolute error for the glass transition temperatures of 19.8 and 26.4 °C was achieved for the test and experimental data sets, respectively. Predictions were made on polymers composed of monomers from four databases that contain biologically accessible small molecules: MetaCyc, MINEs, KEGG, and BiGG. From 1.4 × 106 accessible biobased polymers, we identified five poly(ethylene terephthalate) (PET) analogues with predicted improvements to thermal and transport performance. Experimental validation for one of the PET analogues demonstrated a glass transition temperature between 85 and 112 °C, which is higher than PET and within the predicted range of the PolyID tool. In addition to accurate predictions, we show how the model's predictions are explainable through analysis of individual bond importance for a biobased nylon. Overall, PolyID can aid the biobased polymer practitioner to navigate the vast number of renewable polymers to discover sustainable materials with enhanced performance.
Collapse
Affiliation(s)
- A. Nolan Wilson
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Peter C. St John
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Daniela H. Marin
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Caroline B. Hoyt
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Erik G. Rognerud
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Mark R. Nimlos
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Robin M. Cywar
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Nicholas A. Rorrer
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Kevin M. Shebek
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
- Department
of Chemical and Biological Engineering and Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, United States
- Chemistry
of Life Processes Institute, Northwestern
University, Evanston, Illinois 60208, United States
| | - Linda J. Broadbelt
- Department
of Chemical and Biological Engineering and Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, United States
| | - Gregg T. Beckham
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| | - Michael F. Crowley
- Renewable
Resources and Enabling Sciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, Colorado 80401, United States
| |
Collapse
|
6
|
Griesemer M, Navid A. Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites. Microorganisms 2023; 11:2149. [PMID: 37763993 PMCID: PMC10536367 DOI: 10.3390/microorganisms11092149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 08/07/2023] [Accepted: 08/16/2023] [Indexed: 09/29/2023] Open
Abstract
Secondary metabolites are not essential for the growth of microorganisms, but they play a critical role in how microbes interact with their surroundings. In addition to this important ecological role, secondary metabolites also have a variety of agricultural, medicinal, and industrial uses, and thus the examination of secondary metabolism of plants and microbes is a growing scientific field. While the chemical production of certain secondary metabolites is possible, industrial-scale microbial production is a green and economically attractive alternative. This is even more true, given the advances in bioengineering that allow us to alter the workings of microbes in order to increase their production of compounds of interest. This type of engineering requires detailed knowledge of the "chassis" organism's metabolism. Since the resources and the catalytic capacity of enzymes in microbes is finite, it is important to examine the tradeoffs between various bioprocesses in an engineered system and alter its working in a manner that minimally perturbs the robustness of the system while allowing for the maximum production of a product of interest. The in silico multi-objective analysis of metabolism using genome-scale models is an ideal method for such examinations.
Collapse
Affiliation(s)
| | - Ali Navid
- Lawrence Livermore National Laboratory, Biosciences & Biotechnology Division, Physical & Life Sciences Directorate, Livermore, CA 94550, USA
| |
Collapse
|
7
|
Liu X, Liu H, Zhang Y, Liu C, Liu Y, Li Z, Zhang M. Organic amendments alter microbiota assembly to stimulate soil metabolism for improving soil quality in wheat-maize rotation system. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 339:117927. [PMID: 37075633 DOI: 10.1016/j.jenvman.2023.117927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 03/20/2023] [Accepted: 04/10/2023] [Indexed: 05/03/2023]
Abstract
Straw retention (SR) and organic fertilizer (OF) application contribute to improve soil quality, but it is unclear how the soil microbial assemblage under organic amendments mediate soil biochemical metabolism pathways to perform it. This study collected soil samples from wheat field under different application of fertilizer (chemical fertilizer, as control; SR, and OF) in North China Plain, and systematically investigated the interlinkages among microbe assemblages, metabolites, and physicochemical properties. Results showed that the soil organic carbon (SOC) and permanganate oxidizable organic carbon (LOC) in soil samples followed the trend as OF > SR > control, and the activity of C-acquiring enzymes presented significantly positive correlation with SOC and LOC. In organic amendments, bacteria and fungi community were respectively dominated by deterministic and stochastic processes, while OF exerted more selective pressure on soil microbe. Compared with SR, OF had greater potential to boost the microbial community robustness through increasing the natural connectivity and stimulating fungal taxa activities in inter-kingdom microbial networks. Altogether 67 soil metabolites were significantly affected by organic amendments, most of them belonged to benzenoids (Ben), lipids and lipid-like molecules (LL), and organic acids and derivatives (OA). These metabolites were mainly derived from lipid and amino acid metabolism pathways. A list of keystone genera such as stachybotrys and phytohabitans were identified as important to soil metabolites, SOC, and C-acquiring enzyme activity. Structural equation modeling showed that soil quality properties were closely associated with LL, OA, and PP drove by microbial community assembly and keystone genera. Overall, these findings suggested that straw and organic fertilizer might drive keystone genera dominated by determinism to mediate soil lipid and amino acid metabolism for improving soil quality, which provided new insights into understanding the microbial-mediated biological process in amending soil quality.
Collapse
Affiliation(s)
- Xueqing Liu
- State Key Laboratory of Plant Environmental Resilience, Ministry of Education, Key Laboratory of Farming System, Ministry of Agriculture of China, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Hongrun Liu
- State Key Laboratory of Plant Environmental Resilience, Ministry of Education, Key Laboratory of Farming System, Ministry of Agriculture of China, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Yushi Zhang
- State Key Laboratory of Plant Environmental Resilience, Ministry of Education, Key Laboratory of Farming System, Ministry of Agriculture of China, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
| | - Churong Liu
- State Key Laboratory of Plant Environmental Resilience, Ministry of Education, Key Laboratory of Farming System, Ministry of Agriculture of China, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Yanan Liu
- State Key Laboratory of Plant Environmental Resilience, Ministry of Education, Key Laboratory of Farming System, Ministry of Agriculture of China, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Zhaohu Li
- State Key Laboratory of Plant Environmental Resilience, Ministry of Education, Key Laboratory of Farming System, Ministry of Agriculture of China, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Mingcai Zhang
- State Key Laboratory of Plant Environmental Resilience, Ministry of Education, Key Laboratory of Farming System, Ministry of Agriculture of China, College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China.
| |
Collapse
|
8
|
Investigating the Unique Ability of Trichodesmium To Fix Carbon and Nitrogen Simultaneously Using MiMoSA. mSystems 2023; 8:e0060120. [PMID: 36598239 PMCID: PMC9948733 DOI: 10.1128/msystems.00601-20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
The open ocean is an extremely competitive environment, partially due to the dearth of nutrients. Trichodesmium erythraeum, a marine diazotrophic cyanobacterium, is a keystone species in the ocean due to its ability to fix nitrogen and leak 30 to 50% into the surrounding environment, providing a valuable source of a necessary macronutrient to other species. While there are other diazotrophic cyanobacteria that play an important role in the marine nitrogen cycle, Trichodesmium is unique in its ability to fix both carbon and nitrogen simultaneously during the day without the use of specialized cells called heterocysts to protect nitrogenase from oxygen. Here, we use the advanced modeling framework called multiscale multiobjective systems analysis (MiMoSA) to investigate how Trichodesmium erythraeum can reduce dimolecular nitrogen to ammonium in the presence of oxygen. Our simulations indicate that nitrogenase inhibition is best modeled as Michealis-Menten competitive inhibition and that cells along the filament maintain microaerobia using high flux through Mehler reactions in order to protect nitrogenase from oxygen. We also examined the effect of location on metabolic flux and found that cells at the end of filaments operate in distinctly different metabolic modes than internal cells despite both operating in a photoautotrophic mode. These results give us important insight into how this species is able to operate photosynthesis and nitrogen fixation simultaneously, giving it a distinct advantage over other diazotrophic cyanobacteria because they can harvest light directly to fuel the energy demand of nitrogen fixation. IMPORTANCE Trichodesmium erythraeum is a marine cyanobacterium responsible for approximately half of all biologically fixed nitrogen, making it an integral part of the global nitrogen cycle. Interestingly, unlike other nitrogen-fixing cyanobacteria, Trichodesmium does not use temporal or spatial separation to protect nitrogenase from oxygen poisoning; instead, it operates photosynthesis and nitrogen fixation reactions simultaneously during the day. Unfortunately, the exact mechanism the cells utilize to operate carbon and nitrogen fixation simultaneously is unknown. Here, we use an advanced metabolic modeling framework to investigate and identify the most likely mechanisms Trichodesmium uses to protect nitrogenase from oxygen. The model predicts that cells operate in a microaerobic mode, using both respiratory and Mehler reactions to dramatically reduce intracellular oxygen concentrations.
Collapse
|
9
|
Vidya Muthulakshmi M, Srinivasan A, Srivastava S. Antioxidant Green Factories: Toward Sustainable Production of Vitamin E in Plant In Vitro Cultures. ACS OMEGA 2023; 8:3586-3605. [PMID: 36743063 PMCID: PMC9893489 DOI: 10.1021/acsomega.2c05819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Accepted: 12/14/2022] [Indexed: 06/18/2023]
Abstract
Vitamin E is a dietary supplement synthesized only by photosynthetic organisms and, hence, is an essential vitamin for human well-being. Because of the ever-increasing demand for natural vitamin E and limitations in existing synthesis modes, attempts to improve its yield using plant in vitro cultures have gained traction in recent years. With inflating industrial production costs, integrative approaches to conventional bioprocess optimization is the need of the hour for multifold vitamin E productivity enhancement. In this review, we briefly discuss the structure, isomers, and important metabolic routes of biosynthesis for vitamin E in plants. We then emphasize its vital role in human health and its industrial applications and highlight the market demand and supply. We illustrate the advantages of in vitro plant cell/tissue culture cultivation as an alternative to current commercial production platforms for natural vitamin E. We touch upon the conventional vitamin E metabolic pathway engineering strategies, such as single/multigene overexpression and chloroplast engineering. We highlight the recent progress in plant systems biology to rationally identify metabolic bottlenecks and knockout targets in the vitamin E biosynthetic pathway. We then discuss bioprocess optimization strategies for sustainable vitamin E production, including media/process optimization, precursor/elicitor addition, and scale-up to bioreactors. We culminate the review with a short discussion on kinetic modeling to predict vitamin E production in plant cell cultures and suggestions on sustainable green extraction methods of vitamin E for reduced environmental impact. This review will be of interest to a wider research fraternity, including those from industry and academia working in the field of plant cell biology, plant biotechnology, and bioprocess engineering for phytochemical enhancement.
Collapse
Affiliation(s)
- M. Vidya Muthulakshmi
- Department
of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras (IIT Madras), Chennai, 600 036 Tamil Nadu, India
| | - Aparajitha Srinivasan
- Department
of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras (IIT Madras), Chennai, 600 036 Tamil Nadu, India
| | - Smita Srivastava
- Department
of Biotechnology, Bhupat & Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras (IIT Madras), Chennai, 600 036 Tamil Nadu, India
| |
Collapse
|
10
|
Hissong R, Evans KR, Evans CR. Compound Identification Strategies in Mass Spectrometry-Based Metabolomics and Pharmacometabolomics. Handb Exp Pharmacol 2023; 277:43-71. [PMID: 36409330 DOI: 10.1007/164_2022_617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
The metabolome is composed of a vast array of molecules, including endogenous metabolites and lipids, diet- and microbiome-derived substances, pharmaceuticals and supplements, and exposome chemicals. Correct identification of compounds from this diversity of classes is essential to derive biologically relevant insights from metabolomics data. In this chapter, we aim to provide a practical overview of compound identification strategies for mass spectrometry-based metabolomics, with a particular eye toward pharmacologically-relevant studies. First, we describe routine compound identification strategies applicable to targeted metabolomics. Next, we discuss both experimental (data acquisition-focused) and computational (software-focused) strategies used to identify unknown compounds in untargeted metabolomics data. We then discuss the importance of, and methods for, assessing and reporting the level of confidence of compound identifications. Throughout the chapter, we discuss how these steps can be implemented using today's technology, but also highlight research underway to further improve accuracy and certainty of compound identification. For readers interested in interpreting metabolomics data already collected, this chapter will supply important context regarding the origin of the metabolite names assigned to features in the data and help them assess the certainty of the identifications. For those planning new data acquisition, the chapter supplies guidance for designing experiments and selecting analysis methods to enable accurate compound identification, and it will point the reader toward best-practice data analysis and reporting strategies to allow sound biological and pharmacological interpretation.
Collapse
|
11
|
Mataigne V, Vannier N, Vandenkoornhuyse P, Hacquard S. Multi-genome metabolic modeling predicts functional inter-dependencies in the Arabidopsis root microbiome. MICROBIOME 2022; 10:217. [PMID: 36482420 PMCID: PMC9733318 DOI: 10.1186/s40168-022-01383-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 09/23/2022] [Indexed: 05/28/2023]
Abstract
BACKGROUND From a theoretical ecology point of view, microbiomes are far more complex than expected. Besides competition and competitive exclusion, cooperative microbe-microbe interactions have to be carefully considered. Metabolic dependencies among microbes likely explain co-existence in microbiota. METHODOLOGY In this in silico study, we explored genome-scale metabolic models (GEMs) of 193 bacteria isolated from Arabidopsis thaliana roots. We analyzed their predicted producible metabolites under simulated nutritional constraints including "root exudate-mimicking growth media" and assessed the potential of putative metabolic exchanges of by- and end-products to avoid those constraints. RESULTS We found that the genome-encoded metabolic potential is quantitatively and qualitatively clustered by phylogeny, highlighting metabolic differentiation between taxonomic groups. Random, synthetic combinations of increasing numbers of strains (SynComs) indicated that the number of producible compounds by GEMs increased with average phylogenetic distance, but that most SynComs were centered around an optimal phylogenetic distance. Moreover, relatively small SynComs could reflect the capacity of the whole community due to metabolic redundancy. Inspection of 30 specific end-product metabolites (i.e., target metabolites: amino acids, vitamins, phytohormones) indicated that the majority of the strains had the genetic potential to produce almost all the targeted compounds. Their production was predicted (1) to depend on external nutritional constraints and (2) to be facilitated by nutritional constraints mimicking root exudates, suggesting nutrient availability and root exudates play a key role in determining the number of producible metabolites. An answer set programming solver enabled the identification of numerous combinations of strains predicted to depend on each other to produce these targeted compounds under severe nutritional constraints thus indicating a putative sub-community level of functional redundancy. CONCLUSIONS This study predicts metabolic restrictions caused by available nutrients in the environment. By extension, it highlights the importance of the environment for niche potential, realization, partitioning, and overlap. Our results also suggest that metabolic dependencies and cooperation among root microbiota members compensate for environmental constraints and help maintain co-existence in complex microbial communities. Video Abstract.
Collapse
Affiliation(s)
- Victor Mataigne
- Université de Rennes 1, CNRS, UMR6553 ECOBIO, Campus Beaulieu, 35000, Rennes, France
- Max Planck Institute for Plant Breeding Research, Department of Plant Microbe Interactions, 50829, Cologne, Germany
| | - Nathan Vannier
- Max Planck Institute for Plant Breeding Research, Department of Plant Microbe Interactions, 50829, Cologne, Germany
| | | | - Stéphane Hacquard
- Max Planck Institute for Plant Breeding Research, Department of Plant Microbe Interactions, 50829, Cologne, Germany.
| |
Collapse
|
12
|
Gregersen R, Howarth JD, Wood SA, Vandergoes MJ, Puddick J, Moy C, Li X, Pearman JK, Moody A, Simon KS. Resolving 500 Years of Anthropogenic Impacts in a Mesotrophic Lake: Nutrients Outweigh Other Drivers of Lake Change. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:16940-16951. [PMID: 36379054 DOI: 10.1021/acs.est.2c06835] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Interactions among multiple stressors, legacies of past perturbations, and the lack of historical information make it difficult to determine the influence of individual anthropogenic impacts on lakes and separate them from natural ecosystem variability. In the present study, we coupled paleolimnological approaches, historical data, and ecological experiments to disentangle the impacts of multiple long-term stressors on lake ecosystem structure and function. We found that the lake structure and function remained resistant to the impacts of catchment deforestation and erosion, and the introduction of several exotic fish species. Changes in ecosystem structure and function were consistent, with nutrient enrichment being the primary driver of change. Significant and sustained changes in the lake diatom community structure (and their nutrient requirements), bacterial community function, and paleolimnological proxies of ecosystem function coincided with nitrogen and phosphorus fertilizers in the catchment. The results highlight that the effects of increased nutrient inputs are much stronger than the influence of other, potentially significant, drivers of ecosystem change, and that the degree of nutrient impact can be underestimated by environmental monitoring due to its diffuse and accumulative nature. Delineating the effects of multiple anthropogenic drivers requires long-term records of both impacts and lake ecosystem change across multiple trophic levels.
Collapse
Affiliation(s)
| | | | | | | | | | - Chris Moy
- University of Otago, Dunedin 9016, New Zealand
| | - Xun Li
- GNS Science, Lower Hutt 5040, New Zealand
| | | | | | - Kevin S Simon
- The University of Auckland, Auckland 1010, New Zealand
| |
Collapse
|
13
|
Fregulia P, Campos MM, Dias RJP, Liu J, Guo W, Pereira LGR, Machado MA, Faza DRDLR, Guan LL, Garnsworthy PC, Neves ALA. Taxonomic and predicted functional signatures reveal linkages between the rumen microbiota and feed efficiency in dairy cattle raised in tropical areas. Front Microbiol 2022; 13:1025173. [PMID: 36523842 PMCID: PMC9745175 DOI: 10.3389/fmicb.2022.1025173] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 11/07/2022] [Indexed: 08/27/2023] Open
Abstract
Ruminants digest plant biomass more efficiently than monogastric animals due to their symbiotic relationship with a complex microbiota residing in the rumen environment. What remains unclear is the relationship between the rumen microbial taxonomic and functional composition and feed efficiency (FE), especially in crossbred dairy cattle (Holstein x Gyr) raised under tropical conditions. In this study, we selected twenty-two F1 Holstein x Gyr heifers and grouped them according to their residual feed intake (RFI) ranking, high efficiency (HE) (n = 11) and low efficiency (LE) (n = 11), to investigate the effect of FE on the rumen microbial taxa and their functions. Rumen fluids were collected using a stomach tube apparatus and analyzed using amplicon sequencing targeting the 16S (bacteria and archaea) and 18S (protozoa) rRNA genes. Alpha-diversity and beta-diversity analysis revealed no significant difference in the rumen microbiota between the HE and LE animals. Multivariate analysis (sPLS-DA) showed a clear separation of two clusters in bacterial taxonomic profiles related to each FE group, but in archaeal and protozoal profiles, the clusters overlapped. The sPLS-DA also revealed a clear separation in functional profiles for bacteria, archaea, and protozoa between the HE and LE animals. Microbial taxa were differently related to HE (e.g., Howardella and Shuttleworthia) and LE animals (e.g., Eremoplastron and Methanobrevibacter), and predicted functions were significatively different for each FE group (e.g., K03395-signaling and cellular process was strongly related to HE animals, and K13643-genetic information processing was related to LE animals). This study demonstrates that differences in the rumen microbiome relative to FE ranking are not directly observed from diversity indices (Faith's Phylogenetic Diversity, Pielou's Evenness, Shannon's diversity, weighted UniFrac distance, Jaccard index, and Bray-Curtis dissimilarity), but from targeted identification of specific taxa and microbial functions characterizing each FE group. These results shed light on the role of rumen microbial taxonomic and functional profiles in crossbred Holstein × Gyr dairy cattle raised in tropical conditions, creating the possibility of using the microbial signature of the HE group as a biological tool for the development of biomarkers that improve FE in ruminants.
Collapse
Affiliation(s)
- Priscila Fregulia
- Laboratório de Protozoologia, Instituto de Ciências Biológicas, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil
- Programa de Pós-Graduação em Biodiversidade e Conservação da Natureza, Instituto de Ciências Biológicas, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil
| | - Mariana Magalhães Campos
- Brazilian Agricultural Research Corporation (Empresa Brasileira de Pesquisa Agropecuária, EMBRAPA), National Center for Research on Dairy Cattle, Juiz de Fora, Minas Gerais, Brazil
| | - Roberto Júnio Pedroso Dias
- Laboratório de Protozoologia, Instituto de Ciências Biológicas, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil
- Programa de Pós-Graduação em Biodiversidade e Conservação da Natureza, Instituto de Ciências Biológicas, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais, Brazil
| | - Junhong Liu
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Wei Guo
- Key Laboratory of Animal Genetics, Breeding and Reproduction in the Plateau Mountainous Region, Ministry of Education, Guizhou University, Guiyang, China
| | - Luiz Gustavo Ribeiro Pereira
- Brazilian Agricultural Research Corporation (Empresa Brasileira de Pesquisa Agropecuária, EMBRAPA), National Center for Research on Dairy Cattle, Juiz de Fora, Minas Gerais, Brazil
| | - Marco Antônio Machado
- Brazilian Agricultural Research Corporation (Empresa Brasileira de Pesquisa Agropecuária, EMBRAPA), National Center for Research on Dairy Cattle, Juiz de Fora, Minas Gerais, Brazil
| | - Daniele Ribeiro de Lima Reis Faza
- Brazilian Agricultural Research Corporation (Empresa Brasileira de Pesquisa Agropecuária, EMBRAPA), National Center for Research on Dairy Cattle, Juiz de Fora, Minas Gerais, Brazil
| | - Le Luo Guan
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Phil C. Garnsworthy
- School of Biosciences, University of Nottingham, Loughborough, United Kingdom
| | - André Luis Alves Neves
- Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Frederiksberg, Denmark
| |
Collapse
|
14
|
Yin Y, Song W, Wang J. Inhibitory effect of acetic acid on dark-fermentative hydrogen production. BIORESOURCE TECHNOLOGY 2022; 364:128074. [PMID: 36216278 DOI: 10.1016/j.biortech.2022.128074] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 09/30/2022] [Accepted: 10/02/2022] [Indexed: 06/16/2023]
Abstract
This study examined the working mechanisms of acetic acid inhibition on dark fermentative hydrogen production. It was found that undissociated acetic acid (UAA) concentration was the critical factor in acetic acid inhibition. Hydrogen production activity decreased by 50 % and 90 % when UAA concentrations was 76.3 mg/L (1.27 mmol/L) and 686.7 mg/L (11.44 mmol/L), respectively. Dominant microbes were changed from genus Clostridium_sensu_stricto_1 to genus Inhella, Aquabacterium and Caulobacter under the stress of acetic acid inhibition. Functional enzyme analysis showed that acetic acid inhibited the hydrogen production by activating the lactate formation pathway when UAA concentration was below the inhibition threshold, while by impairing most hydrogen-producing pathways when UAA concentration was over the inhibition threshold. In brief, acetic acid inhibited the hydrogen production by altering the dominant microbial community and regulating the metabolic pathways, controlling the UAA concentration would be a good strategy to alleviate the acetic acid inhibition.
Collapse
Affiliation(s)
- Yanan Yin
- Laboratory of Environmental Technology, INET, Tsinghua University, Beijing 100084, PR China
| | - Weize Song
- Laboratory of Low Carbon Energy, Tsinghua University, Beijing 100084, PR China
| | - Jianlong Wang
- Laboratory of Environmental Technology, INET, Tsinghua University, Beijing 100084, PR China; Beijing Key Laboratory of Radioactive Waste Treatment, INET, Tsinghua University, Beijing 100084, PR China.
| |
Collapse
|
15
|
Passenger Pathogens on Physicians. Am J Infect Control 2022:S0196-6553(22)00759-3. [DOI: 10.1016/j.ajic.2022.10.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 10/13/2022] [Accepted: 10/13/2022] [Indexed: 11/20/2022]
|
16
|
Giuseppe A, Chiara P, Yun N, Igor J. Pathway integration and annotation: building a puzzle with non-matching pieces and no reference picture. Brief Bioinform 2022; 23:6691914. [PMID: 36063560 DOI: 10.1093/bib/bbac368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 07/25/2022] [Accepted: 08/05/2022] [Indexed: 11/13/2022] Open
Abstract
Biological pathways are a broadly used formalism for representing and interpreting the cascade of biochemical reactions underlying cellular and biological mechanisms. Pathway representation provides an ontological link among biomolecules such as RNA, DNA, small molecules, proteins, protein complexes, hormones and genes. Frequently, pathway annotations are used to identify mechanisms linked to genes within affected biological contexts. This important role and the simplicity and elegance in representing complex interactions led to an explosion of pathway representations and databases. Unfortunately, the lack of overlap across databases results in inconsistent enrichment analysis results, unless databases are integrated. However, due to absence of consensus, guidelines or gold standards in pathway definition and representation, integration of data across pathway databases is not straightforward. Despite multiple attempts to provide consolidated pathways, highly related, redundant, poorly overlapping or ambiguous pathways continue to render pathways analysis inconsistent and hard to interpret. Ontology-based integration will promote unbiased, comprehensive yet streamlined analysis of experiments, and will reduce the number of enriched pathways when performing pathway enrichment analysis. Moreover, appropriate and consolidated pathways provide better training data for pathway prediction algorithms. In this manuscript, we describe the current methods for pathway consolidation, their strengths and pitfalls, and highlight directions for future improvements to this research area.
Collapse
Affiliation(s)
- Agapito Giuseppe
- Department of Law, Economics and Social Sciences, University Magna Græcia of Catanzaro, Italy.,Data Analytic Research Center, University Magna Græcia of Catanzaro, Italy
| | - Pastrello Chiara
- Osteoarthritis Research Program, Division of Orthopaedics, Schroeder Arthritis Institute, University Health Network, Toronto, Canada
| | - Niu Yun
- Osteoarthritis Research Program, Division of Orthopaedics, Schroeder Arthritis Institute, University Health Network, Toronto, Canada
| | - Jurisica Igor
- Osteoarthritis Research Program, Division of Orthopaedics, Schroeder Arthritis Institute, University Health Network, Toronto, Canada.,Departments of Medical Biophysics and Computer Science Canada, University of Toronto, Toronto, Canada.,Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Toronto, Canada.,Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia
| |
Collapse
|
17
|
Jackson R, Monnin D, Patapiou PA, Golding G, Helanterä H, Oettler J, Heinze J, Wurm Y, Economou CK, Chapuisat M, Henry LM. Convergent evolution of a labile nutritional symbiosis in ants. THE ISME JOURNAL 2022; 16:2114-2122. [PMID: 35701539 PMCID: PMC9381600 DOI: 10.1038/s41396-022-01256-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/23/2022] [Accepted: 05/26/2022] [Indexed: 01/07/2023]
Abstract
Ants are among the most successful organisms on Earth. It has been suggested that forming symbioses with nutrient-supplementing microbes may have contributed to their success, by allowing ants to invade otherwise inaccessible niches. However, it is unclear whether ants have evolved symbioses repeatedly to overcome the same nutrient limitations. Here, we address this question by comparing the independently evolved symbioses in Camponotus, Plagiolepis, Formica and Cardiocondyla ants. Our analysis reveals the only metabolic function consistently retained in all of the symbiont genomes is the capacity to synthesise tyrosine. We also show that in certain multi-queen lineages that have co-diversified with their symbiont for millions of years, only a fraction of queens carry the symbiont, suggesting ants differ in their colony-level reliance on symbiont-derived resources. Our results imply that symbioses can arise to solve common problems, but hosts may differ in their dependence on symbionts, highlighting the evolutionary forces influencing the persistence of long-term endosymbiotic mutualisms.
Collapse
Affiliation(s)
- Raphaella Jackson
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4NS, UK
| | - David Monnin
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4NS, UK
| | - Patapios A Patapiou
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4NS, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, AL9 7TA, UK
| | - Gemma Golding
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4NS, UK
| | - Heikki Helanterä
- Ecology and Genetics Research Unit, University of Oulu, Oulu, 90014, Finland
- Tvärminne Zoological Station, University of Helsinki, Hanko, Finland
| | - Jan Oettler
- Zoology/Evolutionary Biology, University of Regensburg, Regensburg, 93040, Germany
| | - Jürgen Heinze
- Zoology/Evolutionary Biology, University of Regensburg, Regensburg, 93040, Germany
| | - Yannick Wurm
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4NS, UK
- Alan Turing Institute, London, NW1 2DB, UK
| | - Chloe K Economou
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4NS, UK
| | - Michel Chapuisat
- Department of Ecology and Evolution, University of Lausanne, 1015, Lausanne, Switzerland
| | - Lee M Henry
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E1 4NS, UK.
| |
Collapse
|
18
|
Góngora E, Chen YJ, Ellis M, Okshevsky M, Whyte L. Hydrocarbon bioremediation on Arctic shorelines: Historic perspective and roadway to the future. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 305:119247. [PMID: 35390417 DOI: 10.1016/j.envpol.2022.119247] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 02/26/2022] [Accepted: 03/30/2022] [Indexed: 06/14/2023]
Abstract
Climate change has become one of the greatest concerns of the past few decades. In particular, global warming is a growing threat to the Canadian high Arctic and other polar regions. By the middle of this century, an increase in the annual mean temperature of 1.8 °C-2.7 °C for the Canadian North is predicted. Rising temperatures lead to a significant decrease of the sea ice area covered in the Northwest Passage. As a consequence, a surge of maritime activity in that region increases the risk of hydrocarbon pollution due to accidental fuel spills. In this review, we focus on bioremediation approaches on Arctic shorelines. We summarize historical experimental spill studies conducted at Svalbard, Baffin Island, and the Kerguelen Archipelago, and review contemporary studies that used modern omics techniques in various environments. We discuss how omics approaches can facilitate our understanding of Arctic shoreline bioremediation and identify promising research areas that should be further explored. We conclude that specific environmental conditions strongly alter bioremediation outcomes in Arctic environments and future studies must therefore focus on correlating these diverse parameters with the efficacy of hydrocarbon biodegradation.
Collapse
Affiliation(s)
- Esteban Góngora
- Department of Natural Resource Sciences, McGill University, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada.
| | - Ya-Jou Chen
- Department of Natural Resource Sciences, McGill University, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada
| | - Madison Ellis
- Department of Natural Resource Sciences, McGill University, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada
| | - Mira Okshevsky
- Department of Natural Resource Sciences, McGill University, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada
| | - Lyle Whyte
- Department of Natural Resource Sciences, McGill University, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada
| |
Collapse
|
19
|
Challenges and Limitations of Biological Network Analysis. BIOTECH 2022; 11:biotech11030024. [PMID: 35892929 PMCID: PMC9326688 DOI: 10.3390/biotech11030024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 07/04/2022] [Accepted: 07/06/2022] [Indexed: 11/17/2022] Open
Abstract
High-Throughput technologies are producing an increasing volume of data that needs large amounts of data storage, effective data models and efficient, possibly parallel analysis algorithms. Pathway and interactomics data are represented as graphs and add a new dimension of analysis, allowing, among other features, graph-based comparison of organisms’ properties. For instance, in biological pathway representation, the nodes can represent proteins, RNA and fat molecules, while the edges represent the interaction between molecules. Otherwise, biological networks such as Protein–Protein Interaction (PPI) Networks, represent the biochemical interactions among proteins by using nodes that model the proteins from a given organism, and edges that model the protein–protein interactions, whereas pathway networks enable the representation of biochemical-reaction cascades that happen within the cells or tissues. In this paper, we discuss the main models for standard representation of pathways and PPI networks, the data models for the representation and exchange of pathway and protein interaction data, the main databases in which they are stored and the alignment algorithms for the comparison of pathways and PPI networks of different organisms. Finally, we discuss the challenges and the limitations of pathways and PPI network representation and analysis. We have identified that network alignment presents a lot of open problems worthy of further investigation, especially concerning pathway alignment.
Collapse
|
20
|
Damale MG, Patil R, Ansari SA, Alkahtani HM, Ahmed S, Nur-e-Alam M, Arote R, Sangshetti J. Insilico structure based drug design approach to find potential hits in ventilator-associated pneumonia caused by Pseudomonas aeruginosa. Comput Biol Med 2022; 146:105597. [DOI: 10.1016/j.compbiomed.2022.105597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/20/2022] [Accepted: 05/05/2022] [Indexed: 11/26/2022]
|
21
|
Sarkar I, Sen G, Bhattacharyya S, Gtari M, Sen A. Inter-cluster competition and resource partitioning may govern the ecology of Frankia. Arch Microbiol 2022; 204:326. [PMID: 35576077 DOI: 10.1007/s00203-022-02910-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 04/09/2022] [Accepted: 04/10/2022] [Indexed: 11/25/2022]
Abstract
Microbes live in a complex communal ecosystem. The structural complexity of microbial community reflects diversity, functionality, as well as habitat type. Delineation of ecologically important microbial populations along with exploration of their roles in environmental adaptation or host-microbe interaction has a crucial role in modern microbiology. In this scenario, reverse ecology (the use of genomics to study ecology) plays a pivotal role. Since the co-existence of two different genera in one small niche should maintain a strict direct interaction, it will be interesting to utilize the concept of reverse ecology in this scenario. Here, we exploited an 'R' package, the RevEcoR, to resolve the issue of co-existing microbes which are proven to be a crucial tool for identifying the nature of their relationship (competition or complementation) persisting among them. Our target organism here is Frankia, a nitrogen-fixing actinobacterium popular for its genetic and host-specific nature. According to their plant host, Frankia has already been sub-divided into four clusters C-I, C-II, C-III, and C-IV. Our results revealed a strong competing nature of CI Frankia. Among the clusters of Frankia studied, the competition index between C-I and C-III was the largest. The other interesting result was the co-occurrence of C-II and C-IV groups. It was revealed that these two groups follow the theory of resource partitioning in their lifestyle. Metabolic analysis along with their differential transporter machinery validated our hypothesis of resource partitioning among C-II and C-IV groups.
Collapse
Affiliation(s)
- I Sarkar
- Bioinformatics Facility, University of North Bengal, Siliguri, West Bengal, India
- Department of Botany, University of North Bengal, Siliguri, West Bengal, India
| | - G Sen
- Bioinformatics Facility, University of North Bengal, Siliguri, West Bengal, India
| | - S Bhattacharyya
- Biswa Bangla Genome Centre, Univ. of North Bengal, Siliguri, West Bengal, India
| | - M Gtari
- Unité de Bactériologie Moléculaire and Génomique, Département de Génie Biologique and Chimique, Institut National Des Sciences Appliquéeset de Technologie, Université de Carthage, Carthage, Tunisia
| | - A Sen
- Bioinformatics Facility, University of North Bengal, Siliguri, West Bengal, India.
- Biswa Bangla Genome Centre, Univ. of North Bengal, Siliguri, West Bengal, India.
- Department of Botany, University of North Bengal, Siliguri, West Bengal, India.
| |
Collapse
|
22
|
Cheng M, Liu H, Han M, Li SC, Bu D, Sun S, Hu Z, Yang P, Wang R, Liu Y, Chen F, Peng J, Peng H, Song H, Xia Y, Chu L, Zhou Q, Guan F, Wu J, Tan G, Ning K. Microbiome Resilience and Health Implications for People in Half-Year Travel. Front Immunol 2022; 13:848994. [PMID: 35281043 PMCID: PMC8907539 DOI: 10.3389/fimmu.2022.848994] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 02/07/2022] [Indexed: 12/12/2022] Open
Abstract
Travel entail change in geography and diet, both of which are known as determinant factors in shaping the human gut microbiome. Additionally, altered gut microbiome modulates immunity, bringing about health implications in humans. To explore the effects of the mid-term travel on the gut microbiome, we generated 16S rRNA gene and metagenomic sequencing data from longitudinal samples collected over six months. We monitored dynamic trajectories of the gut microbiome variation of a Chinese volunteer team (VT) in their whole journey to Trinidad and Tobago (TAT). We found gut microbiome resilience that VT’s gut microbial compositions gradually transformed to the local TAT’s enterotypes during their six-month stay in TAT, and then reverted to their original enterotypes after VT’s return to Beijing in one month. Moreover, we identified driven species in this bi-directional plasticity that could play a role in immunity modulation, as exemplified by Bacteroides dorei that attenuated atherosclerotic lesion formation and effectively suppressed proinflammatory immune response. Another driven species P. copri could play a crucial role in rheumatoid arthritis pathogenesis, a chronic autoimmune disease. Carbohydrate-active enzymes are often implicated in immune and host-pathogen interactions, of which glycoside hydrolases were found decreased but glycosyltransferases and carbohydrate esterases increased during the travel; these functions were then restored after VT’ returning to Beijing. Furthermore, we discovered these microbial changes and restoration were mediated by VT people’s dietary changes. These findings indicate that half-year travel leads to change in enterotype and functional patterns, exerting effects on human health. Microbial intervention by dietary guidance in half-year travel would be conducive to immunity modulation for maintaining health.
Collapse
Affiliation(s)
- Mingyue Cheng
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-Imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Hong Liu
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-Imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.,Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Maozhen Han
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-Imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Shuai Cheng Li
- Department of Computer Science, City University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Dongbo Bu
- Key Lab of Intelligent Information Processing, State Lab of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.,School of Computer and Control, University of Chinese Academy of Sciences, Beijing, China
| | - Shiwei Sun
- Key Lab of Intelligent Information Processing, State Lab of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.,School of Computer and Control, University of Chinese Academy of Sciences, Beijing, China
| | - Zhiqiang Hu
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Pengshuo Yang
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-Imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Rui Wang
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Yawen Liu
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Feng Chen
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Jianjun Peng
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Hong Peng
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Hongxing Song
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Yang Xia
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Liqun Chu
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Quan Zhou
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Feng Guan
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Jing Wu
- Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Guangming Tan
- Key Lab of Intelligent Information Processing, State Lab of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.,School of Computer and Control, University of Chinese Academy of Sciences, Beijing, China
| | - Kang Ning
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-Imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China
| |
Collapse
|
23
|
Ke X, Wu H, Chen YX, Guo Y, Yao S, Guo MR, Duan YY, Wang NN, Shi W, Wang C, Dong SS, Kang H, Dai Z, Yang TL. Individualized pathway activity algorithm identifies oncogenic pathways in pan-cancer analysis. EBioMedicine 2022; 79:104014. [PMID: 35487057 PMCID: PMC9117264 DOI: 10.1016/j.ebiom.2022.104014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 04/04/2022] [Accepted: 04/05/2022] [Indexed: 02/07/2023] Open
Abstract
Background Accumulative evidences have shown that dysregulation of biological pathways contributed to the initiation and progression of malignant tumours. Several methods for pathway activity measurement have been proposed, but they are restricted to making comparisons between groups or sensitive to experimental batch effects. Methods We introduced a novel method for individualized pathway activity measurement (IPAM) that is based on the ranking of gene expression levels in individual sample. Taking advantage of IPAM, we calculated the pathway activity of 318 pathways from KEGG database in the 10528 tumour/normal samples of 33 cancer types from TCGA to identify characteristic dysregulated pathways among different cancer types. Findings IPAM precisely quantified the level of activity of each pathway in pan-cancer analysis and exhibited better performance in cancer classification and prognosis prediction over five widely used tools. The average ROC-AUC of cancer diagnostic model using tumour-educated platelets (TEPs) reached 92.84%, suggesting the potential of our algorithm in early diagnosis of cancer. We identified several pathways significantly deregulated and associated with patient survival in a large fraction of cancer types, such as tyrosine metabolism, fatty acid degradation, cell cycle, p53 signalling pathway and DNA replication. We also confirmed the dominant role of metabolic pathways in cancer pathway dysregulation and identified the driving factors of specific pathway dysregulation, such as PPARA for branched-chain amino acid metabolism and NR1I2, NR1I3 for fatty acid metabolism. Interpretation Our study will provide novel clues for understanding the pathological mechanisms of cancer, ultimately paving the way for personalized medicine of cancer. Funding A full list of funding can be found in the Acknowledgements section.
Collapse
Affiliation(s)
- Xin Ke
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Hao Wu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Yi-Xiao Chen
- National and Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi 710004, PR China
| | - Yan Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Shi Yao
- National and Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi 710004, PR China
| | - Ming-Rui Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Yuan-Yuan Duan
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Nai-Ning Wang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Wei Shi
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Chen Wang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Huafeng Kang
- Department of Oncology, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi 710004, PR China
| | - Zhijun Dai
- Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, PR China
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China; National and Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi 710004, PR China.
| |
Collapse
|
24
|
Bauermeister A, Mannochio-Russo H, Costa-Lotufo LV, Jarmusch AK, Dorrestein PC. Mass spectrometry-based metabolomics in microbiome investigations. Nat Rev Microbiol 2022; 20:143-160. [PMID: 34552265 PMCID: PMC9578303 DOI: 10.1038/s41579-021-00621-9] [Citation(s) in RCA: 138] [Impact Index Per Article: 69.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/03/2021] [Indexed: 02/08/2023]
Abstract
Microbiotas are a malleable part of ecosystems, including the human ecosystem. Microorganisms affect not only the chemistry of their specific niche, such as the human gut, but also the chemistry of distant environments, such as other parts of the body. Mass spectrometry-based metabolomics is one of the key technologies to detect and identify the small molecules produced by the human microbiota, and to understand the functional role of these microbial metabolites. This Review provides a foundational introduction to common forms of untargeted mass spectrometry and the types of data that can be obtained in the context of microbiome analysis. Data analysis remains an obstacle; therefore, the emphasis is placed on data analysis approaches and integrative analysis, including the integration of microbiome sequencing data.
Collapse
Affiliation(s)
- Anelize Bauermeister
- Institute of Biomedical Science, Universidade de São Paulo, São Paulo, SP, Brazil,Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA
| | - Helena Mannochio-Russo
- Department of Biochemistry and Organic Chemistry, Institute of Chemistry, São Paulo State University, Araraquara, SP, Brazil,Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA
| | | | - Alan K. Jarmusch
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA
| | - Pieter C. Dorrestein
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA.,Department of Pediatrics, University of California, San Diego, CA, USA.,Center for Microbiome Innovation, University of California, San Diego, CA, USA
| |
Collapse
|
25
|
Low-Cost Algorithms for Metabolic Pathway Pairwise Comparison. Biomimetics (Basel) 2022; 7:biomimetics7010027. [PMID: 35225919 PMCID: PMC8883897 DOI: 10.3390/biomimetics7010027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 01/17/2022] [Accepted: 01/20/2022] [Indexed: 12/10/2022] Open
Abstract
Metabolic pathways provide key information for achieving a better understanding of life and all its processes; this is useful information for the improvement of medicine, agronomy, pharmacy, and other similar areas. The main analysis tool used to study these pathways is based on pathway comparison, using graph data structures. Metabolic pathway comparison has been defined as a computationally complex task. In a previous work, two new algorithms were introduced to treat the problem of metabolic pathway pairwise comparison. Here we provide an extended analysis with more data and a deeper analysis of metabolic pathway comparison as listed in the discussion and results section.
Collapse
|
26
|
Wu X, Cai W, Zhu P, Peng Z, Zheng T, Li D, Li J, Zhou G, Zhang J, Du G. Function-driven design of Bacillus kochii and Filobasidium magnum co-culture to improve quality of flue-cured tobacco. Front Microbiol 2022; 13:1024005. [PMID: 36875537 PMCID: PMC9978371 DOI: 10.3389/fmicb.2022.1024005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 12/16/2022] [Indexed: 02/18/2023] Open
Abstract
Flue-cured tobacco (FCT) is an economical raw material whose quality affects the quality and cost of the derived product. However, the time-consuming and inefficient spontaneous aging is the primary process for improving the FCT quality in the industry. In this study, a function-driven co-culture with functional microorganisms was built in response to the quality-driven need for less irritation and more aroma in FCT. The previous study has found that Bacillus kochii SC could degrade starch and protein to reduce tobacco irritation and off-flavors. The Filobasidium magnum F7 with high lipoxygenase activity was screened out for degrading higher fatty acid esters and terpenoids to promote the aroma and flavor of FCT. Co-cultivation with strain SC and F7 obtained better quality improvement than mono-culture at an initial inoculation ratio of 1:3 for 2 days, representing a significant breakthrough in efficiency and a reduction in production costs compared to the more than 2 years required for the spontaneous aging process. Through the analysis of microbial diversity, predicted flora functions, enzyme activities and volatile compositions within the mono- and co-cultivation, our study showed the formation of a function-driven co-culture between two strains through functional division of labor and nutritional feeding. Herein, the function-driven co-culture via bioaugmentation will become an increasingly implemented approach for the tobacco industry.
Collapse
Affiliation(s)
- Xinying Wu
- School of Biotechnology, Jiangnan University, Wuxi, China.,Science Center for Future Foods, Jiangnan University, Wuxi, China.,School of Liquor and Food Engineering, Guizhou University, Guiyang, China
| | - Wen Cai
- Technical Research Center, China Tobacco Sichuan Industrial Co., Ltd., Chengdu, China
| | - Pengcheng Zhu
- School of Biotechnology, Jiangnan University, Wuxi, China.,Technical Research Center, China Tobacco Sichuan Industrial Co., Ltd., Chengdu, China
| | - Zheng Peng
- School of Biotechnology, Jiangnan University, Wuxi, China.,Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Tianfei Zheng
- School of Biotechnology, Jiangnan University, Wuxi, China.,Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Dongliang Li
- Technical Research Center, China Tobacco Sichuan Industrial Co., Ltd., Chengdu, China
| | - Jianghua Li
- School of Biotechnology, Jiangnan University, Wuxi, China.,Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Guanyu Zhou
- School of Biotechnology, Jiangnan University, Wuxi, China.,Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Juan Zhang
- School of Biotechnology, Jiangnan University, Wuxi, China.,Science Center for Future Foods, Jiangnan University, Wuxi, China
| | - Guocheng Du
- School of Biotechnology, Jiangnan University, Wuxi, China.,The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, China
| |
Collapse
|
27
|
Nzabarushimana E, Tang H. Functional profile of host microbiome indicates Clostridioides difficile infection. Gut Microbes 2022; 14:2135963. [PMID: 36289064 PMCID: PMC9621045 DOI: 10.1080/19490976.2022.2135963] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 09/28/2022] [Accepted: 10/03/2022] [Indexed: 02/04/2023] Open
Abstract
Clostridioides difficile infection (CDI) is a gastro-intestinal (GI) infection that illustrates how perturbations in symbiotic host-microbiome interactions render the GI tract vulnerable to the opportunistic pathogens. CDI also serves as an example of how such perturbations could be reversed via gut microbiota modulation mechanisms, especially fecal microbiota transplantation (FMT). However, microbiome-mediated diagnosis of CDI remains understudied. Here, we evaluated the diagnostic capabilities of the fecal microbiome on the prediction of CDI. We used the metagenomic sequencing data from ten previous studies, encompassing those acquired from CDI patients treated by FMT, CDI-negative patients presenting other intestinal health conditions, and healthy volunteers taking antibiotics. We designed a hybrid species/function profiling approach that determines the abundances of microbial species in the community contributing to its functional profile. These functionally informed taxonomic profiles were then used for classification of the microbial samples. We used logistic regression (LR) models using these features, which showed high prediction accuracy (with an average A U C ≥ 0.91 ), substantiating that the species/function composition of the gut microbiome has a robust diagnostic prediction of CDI. We further assessed the confounding impact of antibiotic therapy on CDI prediction and found that it is distinguishable from the CDI impact. Finally, we devised a log-odds score computed from the output of the LR models to quantify the likelihood of CDI in a gut microbiome sample and applied it to evaluating the effectiveness of FMT based on post-FMT microbiome samples. The results showed that the gut microbiome of patients exhibited a gradual but steady improvement after receiving successful FMT, indicating the restoration of the normal microbiome functions.
Collapse
Affiliation(s)
- Etienne Nzabarushimana
- Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, Indiana, USA
- Division of Gastroenterology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Haixu Tang
- Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, Indiana, USA
| |
Collapse
|
28
|
Casaburi G, Wei J, Kazi S, Liu J, Wang K, Tao GZ, Lin PY, Dunn JCY, Henrick BM, Frese SA, Sylvester KG. Metabolic model of necrotizing enterocolitis in the premature newborn gut resulting from enteric dysbiosis. Front Pediatr 2022; 10:893059. [PMID: 36081629 PMCID: PMC9445129 DOI: 10.3389/fped.2022.893059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 06/24/2022] [Indexed: 11/29/2022] Open
Abstract
Necrotizing enterocolitis (NEC) is a leading cause of premature newborn morbidity and mortality. The clinical features of NEC consistently include prematurity, gut dysbiosis and enteral inflammation, yet the pathogenesis remains obscure. Herein we combine metagenomics and targeted metabolomics, with functional in vivo and in vitro assessment, to define a novel molecular mechanism of NEC. One thousand six hundred and forty seven publicly available metagenomics datasets were analyzed (NEC = 245; healthy = 1,402) using artificial intelligence methodologies. Targeted metabolomic profiling was used to quantify the concentration of specified fecal metabolites at NEC onset (n = 8), during recovery (n = 6), and in age matched controls (n = 10). Toxicity assays of discovered metabolites were performed in vivo in mice and in vitro using human intestinal epithelial cells. Metagenomic and targeted metabolomic analyses revealed significant differences in pyruvate fermentation pathways and associated intermediates. Notably, the short chain fatty acid formate was elevated in the stool of NEC patients at disease onset (P = 0.005) dissipated during recovery (P = 0.02) and positively correlated with degree of intestinal injury (r 2 = 0.86). In vitro, formate caused enterocyte cytotoxicity in human cells through necroptosis (P < 0.01). In vivo, luminal formate caused significant dose and development dependent NEC-like injury in newborn mice. Enterobacter cloacae and Klebsiella pneumoniae were the most discriminatory taxa related to NEC dysbiosis and increased formate production. Together, these data suggest a novel biochemical mechanism of NEC through the microbial production of formate. Clinical efforts to prevent NEC should focus on reducing the functional consequences of newborn gut dysbiosis associated metabolic pathways.
Collapse
Affiliation(s)
| | - Jingjing Wei
- Department of Surgery, Stanford University, Stanford, CA, United States.,Department of Pediatrics, Shanxi Medical University, Taiyuan, China
| | - Sufyan Kazi
- Evolve Biosystems, Inc., Davis, CA, United States
| | - Junlin Liu
- Department of Surgery, Stanford University, Stanford, CA, United States.,Department of General Surgery, The People's Hospital of Liuyang City, Liuyang, China
| | - Kewei Wang
- Department of Surgery, Stanford University, Stanford, CA, United States.,Department of Gastrointestinal Surgery, The First Hospital of China Medical University, Shenyang, China
| | - Guo-Zhong Tao
- Department of Surgery, Stanford University, Stanford, CA, United States
| | - Po-Yu Lin
- Department of Surgery, Stanford University, Stanford, CA, United States
| | - James C Y Dunn
- Department of Surgery, Stanford University, Stanford, CA, United States
| | - Bethany M Henrick
- Evolve Biosystems, Inc., Davis, CA, United States.,Department of Food Science and Technology, University of Nebraska, Lincoln, NE, United States
| | - Steven A Frese
- Evolve Biosystems, Inc., Davis, CA, United States.,Department of Food Science and Technology, University of Nebraska, Lincoln, NE, United States.,Department of Nutrition, University of Nevada Reno, Reno, NV, United States
| | - Karl G Sylvester
- Department of Surgery, Stanford University, Stanford, CA, United States
| |
Collapse
|
29
|
Pettersen VK, Antunes LCM, Dufour A, Arrieta MC. Inferring early-life host and microbiome functions by mass spectrometry-based metaproteomics and metabolomics. Comput Struct Biotechnol J 2021; 20:274-286. [PMID: 35024099 PMCID: PMC8718658 DOI: 10.1016/j.csbj.2021.12.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 12/08/2021] [Accepted: 12/08/2021] [Indexed: 12/17/2022] Open
Abstract
Humans have a long-standing coexistence with microorganisms. In particular, the microbial community that populates the human gastrointestinal tract has emerged as a critical player in governing human health and disease. DNA and RNA sequencing techniques that map taxonomical composition and genomic potential of the gut community have become invaluable for microbiome research. However, deriving a biochemical understanding of how activities of the gut microbiome shape host development and physiology requires an expanded experimental design that goes beyond these approaches. In this review, we explore advances in high-throughput techniques based on liquid chromatography-mass spectrometry. These omics methods for the identification of proteins and metabolites have enabled direct characterisation of gut microbiome functions and the crosstalk with the host. We discuss current metaproteomics and metabolomics workflows for producing functional profiles, the existing methodological challenges and limitations, and recent studies utilising these techniques with a special focus on early life gut microbiome.
Collapse
Affiliation(s)
- Veronika Kuchařová Pettersen
- Research Group for Host-Microbe Interactions, Department of Medical Biology, UiT The Arctic University of Norway, Tromsø, Norway
- Pediatric Research Group, Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway
- Centre for New Antibacterial Strategies, UiT The Arctic University of Norway, Tromsø, Norway
| | - Luis Caetano Martha Antunes
- Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil
- National Institute of Science and Technology of Innovation on Diseases of Neglected Populations, Center for Technological Development in Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil
| | - Antoine Dufour
- Department of Physiology & Pharmacology, University of Calgary, Calgary, Canada
| | - Marie-Claire Arrieta
- Department of Physiology & Pharmacology, University of Calgary, Calgary, Canada
- Department of Pediatrics, University of Calgary, Calgary, AB, Canada
- International Microbiome Centre, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| |
Collapse
|
30
|
Chacko S, Haseeb YB, Haseeb S. Metabolomics Work Flow and Analytics in Systems Biology. Curr Mol Med 2021; 22:870-881. [PMID: 34923941 DOI: 10.2174/1566524022666211217102105] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 08/26/2021] [Accepted: 09/24/2021] [Indexed: 11/22/2022]
Abstract
Metabolomics is an omics approach of systems biology that involves the development and assessment of large-scale, comprehensive biochemical analysis tools for metabolites in biological systems. This review describes the metabolomics workflow and provides an overview of current analytic tools used for the quantification of metabolic profiles. We explain analytic tools such as mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, ionization techniques, and approaches for data extraction and analysis.
Collapse
Affiliation(s)
- Sanoj Chacko
- Division of Cardiology, Queen's University, Kingston, Ontario, Canada
| | - Yumna B Haseeb
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, Ontario, Canada
| | - Sohaib Haseeb
- Division of Cardiology, Queen's University, Kingston, Ontario, Canada
| |
Collapse
|
31
|
Cheng M, Ge X, Zhong C, Fu R, Ning K, Xu S. Micro-coevolution of host genetics with gut microbiome in three Chinese ethnic groups. J Genet Genomics 2021; 48:972-983. [PMID: 34562635 DOI: 10.1016/j.jgg.2021.09.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 09/03/2021] [Accepted: 09/06/2021] [Indexed: 12/23/2022]
Abstract
Understanding the micro-coevolution of the human gut microbiome with host genetics is challenging but essential in both evolutionary and medical studies. To gain insight into the interactions between host genetic variation and the gut microbiome, we analyzed both the human genome and gut microbiome collected from a cohort of 190 students in the same boarding college and representing 3 ethnic groups, Uyghur, Kazakh, and Han Chinese. We found that differences in gut microbiome were greater between genetically distinct ethnic groups than those genetically closely related ones in taxonomic composition, functional composition, enterotype stratification, and microbiome genetic differentiation. We also observed considerable correlations between host genetic variants and the abundance of a subset of gut microbial species. Notably, interactions between gut microbiome species and host genetic variants might have coordinated effects on specific human phenotypes. Bacteroides ovatus, previously reported to modulate intestinal immunity, is significantly correlated with the host genetic variant rs12899811 (meta-P = 5.55 × 10-5), which regulates the VPS33B expression in the colon, acting as a tumor suppressor of colorectal cancer. These results advance our understanding of the micro-coevolution of the human gut microbiome and their interactive effects with host genetic variation on phenotypic diversity.
Collapse
Affiliation(s)
- Mingyue Cheng
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Xueling Ge
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Chaofang Zhong
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Ruiqing Fu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Kang Ning
- Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center of AI Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Shuhua Xu
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China; Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450052, China; Human Phenome Institute, Fudan University, Shanghai 201203, China.
| |
Collapse
|
32
|
GPRuler: Metabolic gene-protein-reaction rules automatic reconstruction. PLoS Comput Biol 2021; 17:e1009550. [PMID: 34748537 PMCID: PMC8601613 DOI: 10.1371/journal.pcbi.1009550] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 11/18/2021] [Accepted: 10/11/2021] [Indexed: 11/19/2022] Open
Abstract
Metabolic network models are increasingly being used in health care and industry. As a consequence, many tools have been released to automate their reconstruction process de novo. In order to enable gene deletion simulations and integration of gene expression data, these networks must include gene-protein-reaction (GPR) rules, which describe with a Boolean logic relationships between the gene products (e.g., enzyme isoforms or subunits) associated with the catalysis of a given reaction. Nevertheless, the reconstruction of GPRs still remains a largely manual and time consuming process. Aiming at fully automating the reconstruction process of GPRs for any organism, we propose the open-source python-based framework GPRuler. By mining text and data from 9 different biological databases, GPRuler can reconstruct GPRs starting either from just the name of the target organism or from an existing metabolic model. The performance of the developed tool is evaluated at small-scale level for a manually curated metabolic model, and at genome-scale level for three metabolic models related to Homo sapiens and Saccharomyces cerevisiae organisms. By exploiting these models as benchmarks, the proposed tool shown its ability to reproduce the original GPR rules with a high level of accuracy. In all the tested scenarios, after a manual investigation of the mismatches between the rules proposed by GPRuler and the original ones, the proposed approach revealed to be in many cases more accurate than the original models. By complementing existing tools for metabolic network reconstruction with the possibility to reconstruct GPRs quickly and with a few resources, GPRuler paves the way to the study of context-specific metabolic networks, representing the active portion of the complete network in given conditions, for organisms of industrial or biomedical interest that have not been characterized metabolically yet.
Collapse
|
33
|
Patel MK, Pandey S, Kumar M, Haque MI, Pal S, Yadav NS. Plants Metabolome Study: Emerging Tools and Techniques. PLANTS (BASEL, SWITZERLAND) 2021; 10:2409. [PMID: 34834772 PMCID: PMC8621461 DOI: 10.3390/plants10112409] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 10/31/2021] [Accepted: 11/01/2021] [Indexed: 05/06/2023]
Abstract
Metabolomics is now considered a wide-ranging, sensitive and practical approach to acquire useful information on the composition of a metabolite pool present in any organism, including plants. Investigating metabolomic regulation in plants is essential to understand their adaptation, acclimation and defense responses to environmental stresses through the production of numerous metabolites. Moreover, metabolomics can be easily applied for the phenotyping of plants; and thus, it has great potential to be used in genome editing programs to develop superior next-generation crops. This review describes the recent analytical tools and techniques available to study plants metabolome, along with their significance of sample preparation using targeted and non-targeted methods. Advanced analytical tools, like gas chromatography-mass spectrometry (GC-MS), liquid chromatography mass-spectroscopy (LC-MS), capillary electrophoresis-mass spectrometry (CE-MS), fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) matrix-assisted laser desorption/ionization (MALDI), ion mobility spectrometry (IMS) and nuclear magnetic resonance (NMR) have speed up precise metabolic profiling in plants. Further, we provide a complete overview of bioinformatics tools and plant metabolome database that can be utilized to advance our knowledge to plant biology.
Collapse
Affiliation(s)
- Manish Kumar Patel
- Department of Postharvest Science of Fresh Produce, Agricultural Research Organization, Volcani Center, Rishon LeZion 7505101, Israel
| | - Sonika Pandey
- Independent Researcher, Civil Line, Fathepur 212601, India;
| | - Manoj Kumar
- Institute of Plant Sciences, Agricultural Research Organization, Volcani Center, Rishon LeZion 7505101, Israel;
| | - Md Intesaful Haque
- Fruit Tree Science Department, Newe Ya’ar Research Center, Agriculture Research Organization, Volcani Center, Ramat Yishay 3009500, Israel;
| | - Sikander Pal
- Plant Physiology Laboratory, Department of Botany, University of Jammu, Jammu 180006, India;
| | - Narendra Singh Yadav
- Department of Biological Sciences, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
| |
Collapse
|
34
|
Agapito G, Cannataro M. Using BioPAX-Parser (BiP) to enrich lists of genes or proteins with pathway data. BMC Bioinformatics 2021; 22:376. [PMID: 34592927 PMCID: PMC8482563 DOI: 10.1186/s12859-021-04297-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 07/06/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Pathway enrichment analysis (PEA) is a well-established methodology for interpreting a list of genes and proteins of interest related to a condition under investigation. This paper aims to extend our previous work in which we introduced a preliminary comparative analysis of pathway enrichment analysis tools. We extended the earlier work by providing more case studies, comparing BiP enrichment performance with other well-known PEA software tools. METHODS PEA uses pathway information to discover connections between a list of genes and proteins as well as biological mechanisms, helping researchers to overcome the problem of explaining biological entity lists of interest disconnected from the biological context. RESULTS We compared the results of BiP with some existing pathway enrichment analysis tools comprising Centrality-based Pathway Enrichment, pathDIP, and Signaling Pathway Impact Analysis, considering three cancer types (colorectal, endometrial, and thyroid), for a total of six datasets (that is, two datasets per cancer type) obtained from the The Cancer Genome Atlas and Gene Expression Omnibus databases. We measured the similarities between the overlap of the enrichment results obtained using each couple of cancer datasets related to the same cancer. CONCLUSION As a result, BiP identified some well-known pathways related to the investigated cancer type, validated by the available literature. We also used the Jaccard and meet-min indices to evaluate the stability and the similarity between the enrichment results obtained from each couple of cancer datasets. The obtained results show that BiP provides more stable enrichment results than other tools.
Collapse
Affiliation(s)
- Giuseppe Agapito
- Department of Legal, Economic and Social Sciences, University "Magna Graecia", Catanzaro, Italy. .,Data Analytics Research Center, University "Magna Graecia", Catanzaro, Italy.
| | - Mario Cannataro
- Department of Medical and Surgical Sciences, University "Magna Graecia", Catanzaro, Italy. .,Data Analytics Research Center, University "Magna Graecia", Catanzaro, Italy.
| |
Collapse
|
35
|
Seif Y, Palsson BØ. Path to improving the life cycle and quality of genome-scale models of metabolism. Cell Syst 2021; 12:842-859. [PMID: 34555324 PMCID: PMC8480436 DOI: 10.1016/j.cels.2021.06.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 02/17/2021] [Accepted: 06/23/2021] [Indexed: 11/28/2022]
Abstract
Genome-scale models of metabolism (GEMs) are key computational tools for the systems-level study of metabolic networks. Here, we describe the "GEM life cycle," which we subdivide into four stages: inception, maturation, specialization, and amalgamation. We show how different types of GEM reconstruction workflows fit in each stage and proceed to highlight two fundamental bottlenecks for GEM quality improvement: GEM maturation and content removal. We identify common characteristics contributing to increasing quality of maturing GEMs drawing from past independent GEM maturation efforts. We then shed some much-needed light on the latent and unrecognized but pervasive issue of content removal, demonstrating the substantial effects of model pruning on its solution space. Finally, we propose a novel framework for content removal and associated confidence-level assignment which will help guide future GEM development efforts, reduce duplication of effort across groups, potentially aid automated reconstruction platforms, and boost the reproducibility of model development.
Collapse
Affiliation(s)
- Yara Seif
- Department of Bioengineering, University of California, San Diego, La Jolla, San Diego, CA 92093, USA
| | - Bernhard Ørn Palsson
- Department of Bioengineering, University of California, San Diego, La Jolla, San Diego, CA 92093, USA.
| |
Collapse
|
36
|
Macrofungi Cultivation in Shady Forest Areas Significantly Increases Microbiome Diversity, Abundance and Functional Capacity in Soil Furrows. J Fungi (Basel) 2021; 7:jof7090775. [PMID: 34575813 PMCID: PMC8469386 DOI: 10.3390/jof7090775] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 09/10/2021] [Accepted: 09/10/2021] [Indexed: 12/18/2022] Open
Abstract
Cultivating macrofungi is an important management measure to develop economy in shady forest areas; however, its effect on soil ecology, especially microbial abundance and structure, remains insufficiently studied. Herein, in a subtropical forestland, soil chemical and enzyme analyses, metagenomic sequencing and quantitative real-time PCR were employed to evaluate the impact of Stropharia rugosoannulata cultivation on soil microbiomes in three niches: soil below fungal beds, soil from furrows, and control forest soil with no influence from mushroom cultivation. Nutrients were accumulated in the soil below fungal beds with a significant increase (p < 0.05) in SOC, total C, total N, available P, and the activities of glucosidase and cellobiosidase. Non-metric multidimensional scaling and PERMANOVA results indicated that the structure of the microbiomes had been significantly (p < 0.05) shaped among the different niches. Soil furrows were microbial hotspots characterized by the higher microbial diversity and richness. Moreover, the increased microbiome abundance (assessed through qPCR) and the high number of significant stimulated functional types (based on MetaCyc genome database) indicated an enhanced functional capacity in furrows. Together, these results provide a comprehensive understanding of the microbial assemblies and the differently influenced soil properties in mushroom cultivation areas.
Collapse
|
37
|
Oftadeh O, Salvy P, Masid M, Curvat M, Miskovic L, Hatzimanikatis V. A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics. Nat Commun 2021; 12:4790. [PMID: 34373465 PMCID: PMC8352978 DOI: 10.1038/s41467-021-25158-6] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 07/22/2021] [Indexed: 02/07/2023] Open
Abstract
Eukaryotic organisms play an important role in industrial biotechnology, from the production of fuels and commodity chemicals to therapeutic proteins. To optimize these industrial systems, a mathematical approach can be used to integrate the description of multiple biological networks into a single model for cell analysis and engineering. One of the most accurate models of biological systems include Expression and Thermodynamics FLux (ETFL), which efficiently integrates RNA and protein synthesis with traditional genome-scale metabolic models. However, ETFL is so far only applicable for E. coli. To adapt this model for Saccharomyces cerevisiae, we developed yETFL, in which we augmented the original formulation with additional considerations for biomass composition, the compartmentalized cellular expression system, and the energetic costs of biological processes. We demonstrated the ability of yETFL to predict maximum growth rate, essential genes, and the phenotype of overflow metabolism. We envision that the presented formulation can be extended to a wide range of eukaryotic organisms to the benefit of academic and industrial research.
Collapse
Affiliation(s)
- Omid Oftadeh
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Pierre Salvy
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Cambrium GmbH, Berlin, Germany
| | - Maria Masid
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Maxime Curvat
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Quotient Suisse SA, Eysins, Switzerland
| | - Ljubisa Miskovic
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Vassily Hatzimanikatis
- Laboratory of Computational Systems Biotechnology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| |
Collapse
|
38
|
Shah HA, Liu J, Yang Z, Feng J. Review of Machine Learning Methods for the Prediction and Reconstruction of Metabolic Pathways. Front Mol Biosci 2021; 8:634141. [PMID: 34222327 PMCID: PMC8247443 DOI: 10.3389/fmolb.2021.634141] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 06/01/2021] [Indexed: 11/13/2022] Open
Abstract
Prediction and reconstruction of metabolic pathways play significant roles in many fields such as genetic engineering, metabolic engineering, drug discovery, and are becoming the most active research topics in synthetic biology. With the increase of related data and with the development of machine learning techniques, there have many machine leaning based methods been proposed for prediction or reconstruction of metabolic pathways. Machine learning techniques are showing state-of-the-art performance to handle the rapidly increasing volume of data in synthetic biology. To support researchers in this field, we briefly review the research progress of metabolic pathway reconstruction and prediction based on machine learning. Some challenging issues in the reconstruction of metabolic pathways are also discussed in this paper.
Collapse
Affiliation(s)
- Hayat Ali Shah
- Institute of Artificial Intelligence, School of Computer Science, Wuhan University, Wuhan, China
| | - Juan Liu
- Institute of Artificial Intelligence, School of Computer Science, Wuhan University, Wuhan, China
| | - Zhihui Yang
- Institute of Artificial Intelligence, School of Computer Science, Wuhan University, Wuhan, China
| | - Jing Feng
- Institute of Artificial Intelligence, School of Computer Science, Wuhan University, Wuhan, China
| |
Collapse
|
39
|
Low A, Soh M, Miyake S, Aw VZJ, Feng J, Wong A, Seedorf H. Longitudinal Changes in Diet Cause Repeatable and Largely Reversible Shifts in Gut Microbial Communities of Laboratory Mice and Are Observed across Segments of the Entire Intestinal Tract. Int J Mol Sci 2021; 22:5981. [PMID: 34205981 PMCID: PMC8198505 DOI: 10.3390/ijms22115981] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 05/27/2021] [Accepted: 05/27/2021] [Indexed: 01/04/2023] Open
Abstract
Dietary changes are known to alter the composition of the gut microbiome. However, it is less understood how repeatable and reversible these changes are and how diet switches affect the microbiota in the various segments of the gastrointestinal tract. Here, a treatment group of conventionally raised laboratory mice is subjected to two periods of western diet (WD) interrupted by a period of standard diet (SD) of the same duration. Beta-diversity analyses show that diet-induced microbiota changes are largely reversible (q = 0.1501; PERMANOVA, weighted-UniFrac comparison of the treatment-SD group to the control-SD group) and repeatable (q = 0.032; PERMANOVA, weighted-UniFrac comparison of both WD treatments). Furthermore, we report that diet switches alter the gut microbiota composition along the length of the intestinal tract in a segment-specific manner, leading to gut segment-specific Firmicutes/Bacteroidota ratios. We identified prevalent and distinct Amplicon Sequencing Variants (ASVs), particularly in genera of the recently described Muribaculaceae, along the gut as well as ASVs that are differentially abundant between segments of treatment and control groups. Overall, this study provides insights into the reversibility of diet-induced microbiota changes and highlights the importance of expanding sampling efforts beyond the collections of fecal samples to characterize diet-dependent and segment-specific microbiome differences.
Collapse
Affiliation(s)
- Adrian Low
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore 117604, Singapore; (A.L.); (M.S.); (S.M.); (V.Z.J.A.); (J.F.); (A.W.)
| | - Melissa Soh
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore 117604, Singapore; (A.L.); (M.S.); (S.M.); (V.Z.J.A.); (J.F.); (A.W.)
| | - Sou Miyake
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore 117604, Singapore; (A.L.); (M.S.); (S.M.); (V.Z.J.A.); (J.F.); (A.W.)
| | - Vanessa Zhi Jie Aw
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore 117604, Singapore; (A.L.); (M.S.); (S.M.); (V.Z.J.A.); (J.F.); (A.W.)
| | - Jian Feng
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore 117604, Singapore; (A.L.); (M.S.); (S.M.); (V.Z.J.A.); (J.F.); (A.W.)
| | - Adeline Wong
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore 117604, Singapore; (A.L.); (M.S.); (S.M.); (V.Z.J.A.); (J.F.); (A.W.)
| | - Henning Seedorf
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore 117604, Singapore; (A.L.); (M.S.); (S.M.); (V.Z.J.A.); (J.F.); (A.W.)
- Department of Biological Sciences, National University of Singapore, Singapore 117604, Singapore
| |
Collapse
|
40
|
Ankrah NYD, Barker BE, Song J, Wu C, McMullen JG, Douglas AE. Predicted Metabolic Function of the Gut Microbiota of Drosophila melanogaster. mSystems 2021. [PMID: 33947801 DOI: 10.1101/2021.01.20.427455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023] Open
Abstract
An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and their impact on host physiology. This research can be confounded by poorly understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multiway interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition, and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that, in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle, including 2-oxoglutarate and succinate, are produced at high flux and cross-fed between bacterial taxa, suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.IMPORTANCE Drosophila is an important model for microbiome research partly because of the low complexity of its mostly culturable gut microbiota. Our current understanding of how Drosophila interacts with its gut microbes and how these interactions influence host traits derives almost entirely from empirical studies that focus on individual microbial taxa or classes of metabolites. These studies have failed to capture fully the complexity of metabolic interactions that occur between host and microbe. To overcome this limitation, we reconstructed and analyzed 31 metabolic models for every combination of the five principal bacterial taxa in the gut microbiome of Drosophila This revealed that metabolic interactions between Drosophila gut bacterial taxa are highly dynamic and influenced by cooccurring bacteria and nutrient availability. Our results generate testable hypotheses about among-microbe ecological interactions in the Drosophila gut and the diversity of metabolites available to influence host traits.
Collapse
Affiliation(s)
- Nana Y D Ankrah
- Department of Entomology, Cornell University, Ithaca, New York, USA
| | - Brandon E Barker
- Center for Advanced Computing, Cornell University, Ithaca, New York, USA
| | - Joan Song
- School of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
| | - Cindy Wu
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, USA
| | - John G McMullen
- Department of Entomology, Cornell University, Ithaca, New York, USA
| | - Angela E Douglas
- Department of Entomology, Cornell University, Ithaca, New York, USA
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, USA
| |
Collapse
|
41
|
Ankrah NYD, Barker BE, Song J, Wu C, McMullen JG, Douglas AE. Predicted Metabolic Function of the Gut Microbiota of Drosophila melanogaster. mSystems 2021; 6:e01369-20. [PMID: 33947801 PMCID: PMC8269265 DOI: 10.1128/msystems.01369-20] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 04/01/2021] [Indexed: 12/28/2022] Open
Abstract
An important goal for many nutrition-based microbiome studies is to identify the metabolic function of microbes in complex microbial communities and their impact on host physiology. This research can be confounded by poorly understood effects of community composition and host diet on the metabolic traits of individual taxa. Here, we investigated these multiway interactions by constructing and analyzing metabolic models comprising every combination of five bacterial members of the Drosophila gut microbiome (from single taxa to the five-member community of Acetobacter and Lactobacillus species) under three nutrient regimes. We show that the metabolic function of Drosophila gut bacteria is dynamic, influenced by community composition, and responsive to dietary modulation. Furthermore, we show that ecological interactions such as competition and mutualism identified from the growth patterns of gut bacteria are underlain by a diversity of metabolic interactions, and show that the bacteria tend to compete for amino acids and B vitamins more frequently than for carbon sources. Our results reveal that, in addition to fermentation products such as acetate, intermediates of the tricarboxylic acid (TCA) cycle, including 2-oxoglutarate and succinate, are produced at high flux and cross-fed between bacterial taxa, suggesting important roles for TCA cycle intermediates in modulating Drosophila gut microbe interactions and the potential to influence host traits. These metabolic models provide specific predictions of the patterns of ecological and metabolic interactions among gut bacteria under different nutrient regimes, with potentially important consequences for overall community metabolic function and nutritional interactions with the host.IMPORTANCE Drosophila is an important model for microbiome research partly because of the low complexity of its mostly culturable gut microbiota. Our current understanding of how Drosophila interacts with its gut microbes and how these interactions influence host traits derives almost entirely from empirical studies that focus on individual microbial taxa or classes of metabolites. These studies have failed to capture fully the complexity of metabolic interactions that occur between host and microbe. To overcome this limitation, we reconstructed and analyzed 31 metabolic models for every combination of the five principal bacterial taxa in the gut microbiome of Drosophila This revealed that metabolic interactions between Drosophila gut bacterial taxa are highly dynamic and influenced by cooccurring bacteria and nutrient availability. Our results generate testable hypotheses about among-microbe ecological interactions in the Drosophila gut and the diversity of metabolites available to influence host traits.
Collapse
Affiliation(s)
- Nana Y D Ankrah
- Department of Entomology, Cornell University, Ithaca, New York, USA
| | - Brandon E Barker
- Center for Advanced Computing, Cornell University, Ithaca, New York, USA
| | - Joan Song
- School of Electrical and Computer Engineering, Cornell University, Ithaca, New York, USA
| | - Cindy Wu
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York, USA
| | - John G McMullen
- Department of Entomology, Cornell University, Ithaca, New York, USA
| | - Angela E Douglas
- Department of Entomology, Cornell University, Ithaca, New York, USA
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, USA
| |
Collapse
|
42
|
Sheoran S, Kumar S, Kumar P, Meena RS, Rakshit S. Nitrogen fixation in maize: breeding opportunities. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2021; 134:1263-1280. [PMID: 33677701 DOI: 10.1007/s00122-021-03791-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 02/06/2021] [Indexed: 06/12/2023]
Abstract
Maize (Zea mays L.) is a highly versatile crop with huge demand of nitrogen (N) for its growth and development. N is the most essential macronutrient for crop production. Despite being the highest abundant element in the atmosphere (~ 78%), it is scarcely available for plant growth. To fulfil the N demand, commercial agriculture is largely dependent on synthetic fertilizers. Excessive dependence on inorganic fertilizers has created extensive ecological as well as economic problems worldwide. Hence, for a sustainable solution to nitrogenous fertilizer use, development of biological nitrogen fixation (BNF) in cereals will be the best alternative. BNF is a well-known mechanism in legumes where diazotrophs convert atmospheric nitrogen (N≡N) to plant-available form, ammonium (NH4+). From many decades, researchers have dreamt to develop a similar symbiotic partnership as in legumes to the cereal crops. A large number of endophytic diazotrophs have been found associated with maize. Elucidation of the genetic and molecular aspects of their interaction will open up new avenues to introgress BNF in maize breeding. With the advanced understanding of N-fixation process, researchers are at a juncture of breeding and engineering this symbiotic relationships in cereals. Different breeding, genetic engineering, omics, gene editing, and synthetic biology approaches will be discussed in this review to make BNF a reality in cereals. It will help to provide a road map to develop/improve the BNF in maize to an advance step for the sustainable production system to achieve the food and nutritional security.
Collapse
Affiliation(s)
- Seema Sheoran
- ICAR-Indian Institute of Maize Research, PAU Campus, Ludhiana, 1410 04, India
| | - Sandeep Kumar
- ICAR-Indian Institute of Pulses Research, Regional Station, Phanda, Bhopal, 462 030, India
| | - Pradeep Kumar
- ICAR-Indian Institute of Maize Research, PAU Campus, Ludhiana, 1410 04, India
| | - Ram Swaroop Meena
- Department of Agronomy, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, 221 005, India
| | - Sujay Rakshit
- ICAR-Indian Institute of Maize Research, PAU Campus, Ludhiana, 1410 04, India.
| |
Collapse
|
43
|
Salvato F, Hettich RL, Kleiner M. Five key aspects of metaproteomics as a tool to understand functional interactions in host-associated microbiomes. PLoS Pathog 2021; 17:e1009245. [PMID: 33630960 PMCID: PMC7906368 DOI: 10.1371/journal.ppat.1009245] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Affiliation(s)
- Fernanda Salvato
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, United States of America
- * E-mail: (FS); (MK)
| | - Robert L. Hettich
- Oak Ridge National Laboratory, Biosciences Division, Oak Ridge, Tennessee, United States of America
| | - Manuel Kleiner
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, North Carolina, United States of America
- * E-mail: (FS); (MK)
| |
Collapse
|
44
|
The Metano Modeling Toolbox MMTB: An Intuitive, Web-Based Toolbox Introduced by Two Use Cases. Metabolites 2021; 11:metabo11020113. [PMID: 33671140 PMCID: PMC7923039 DOI: 10.3390/metabo11020113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 02/12/2021] [Accepted: 02/15/2021] [Indexed: 11/17/2022] Open
Abstract
Genome-scale metabolic models are of high interest in a number of different research fields. Flux balance analysis (FBA) and other mathematical methods allow the prediction of the steady-state behavior of metabolic networks under different environmental conditions. However, many existing applications for flux optimizations do not provide a metabolite-centric view on fluxes. Metano is a standalone, open-source toolbox for the analysis and refinement of metabolic models. While flux distributions in metabolic networks are predominantly analyzed from a reaction-centric point of view, the Metano methods of split-ratio analysis and metabolite flux minimization also allow a metabolite-centric view on flux distributions. In addition, we present MMTB (Metano Modeling Toolbox), a web-based toolbox for metabolic modeling including a user-friendly interface to Metano methods. MMTB assists during bottom-up construction of metabolic models by integrating reaction and enzymatic annotation data from different databases. Furthermore, MMTB is especially designed for non-experienced users by providing an intuitive interface to the most commonly used modeling methods and offering novel visualizations. Additionally, MMTB allows users to upload their models, which can in turn be explored and analyzed by the community. We introduce MMTB by two use cases, involving a published model of Corynebacterium glutamicum and a newly created model of Phaeobacter inhibens.
Collapse
|
45
|
Li L, Ning D, Jeon Y, Ryu H, Santo Domingo JW, Kang DW, Kadudula A, Seo Y. Ecological insights into assembly processes and network structures of bacterial biofilms in full-scale biologically active carbon filters under ozone implementation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 751:141409. [PMID: 32882545 PMCID: PMC8273922 DOI: 10.1016/j.scitotenv.2020.141409] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Revised: 07/28/2020] [Accepted: 07/30/2020] [Indexed: 06/11/2023]
Abstract
To address the adverse effects of harmful algal blooms, there are increased demands over the implementation of ozone coupled with biologically active carbon (BAC) filters in the drinking water treatment plants. Although the microbial biofilms are vital elements to support the proper performance of BAC filters, except for taxonomic affiliations, little is known about the assembly mechanisms of microbial communities in the full-scale BAC filters. This study aimed to examine how the assembly processes and their associated factors (e.g., influent characteristics, biological interactions) drive the temporal dynamics of bacterial communities in full-scale BAC filters, which underwent ozone implementation (five consecutive seasons from 2017 to 2018). The results revealed that along with the increase of bacterial taxonomic richness and evenness, stochastic processes became more crucial to determine the bacterial community assembly in the summer and autumn after ozone implementation (relative contribution: 61.23% and 83.75%, respectively). Moreover, their corresponding networks possessed simple network structures with lower modularity than other seasons, which implied lesser biological interactions among bacterial populations. The correlation between taxonomic and predicted functional diversities using functional redundancy index indicated that relatively high levels of bacterial functional redundancy (>0.83) were generally present in BAC filters. However, compared to other seasons, significantly higher degrees of functional redundancy existed in the summer and autumn after ozone implementation (0.85 ± 0.01 and 0.86 ± 0.01, respectively). Overall, this work improves our understanding of the microbial ecology of full-scale BAC filters by providing a conceptual framework that characterizes bacterial biofilm assembly processes relevant to performance optimization of full-scale BAC filters.
Collapse
Affiliation(s)
- Lei Li
- Department of Civil and Environmental Engineering, University of Toledo, Mail Stop 307, 3048 Nitschke Hall, Toledo, OH, USA
| | - Daliang Ning
- Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK, USA
| | - Youchul Jeon
- Department of Civil and Environmental Engineering, University of Toledo, Mail Stop 307, 3048 Nitschke Hall, Toledo, OH, USA
| | - Hodon Ryu
- Water Infrastructure Division, Center for Environmental Solutions and Emergency Response, U.S. Environmental Protection Agency, Cincinnati, OH 45268, USA
| | - Jorge W Santo Domingo
- Water Infrastructure Division, Center for Environmental Solutions and Emergency Response, U.S. Environmental Protection Agency, Cincinnati, OH 45268, USA
| | - Dae-Wook Kang
- Department of Civil and Environmental Engineering, University of Toledo, Mail Stop 307, 3048 Nitschke Hall, Toledo, OH, USA
| | - Anusha Kadudula
- Department of Civil and Environmental Engineering, University of Toledo, Mail Stop 307, 3048 Nitschke Hall, Toledo, OH, USA
| | - Youngwoo Seo
- Department of Civil and Environmental Engineering, University of Toledo, Mail Stop 307, 3048 Nitschke Hall, Toledo, OH, USA; Department of Chemical Engineering, University of Toledo, Mail Stop 307, 3048 Nitschke Hall, Toledo, OH, USA.
| |
Collapse
|
46
|
Copeland JK, Chao G, Vanderhout S, Acton E, Wang PW, Benchimol EI, El-Sohemy A, Croitoru K, Gommerman JL, Guttman DS. The Impact of Migration on the Gut Metagenome of South Asian Canadians. Gut Microbes 2021; 13:1-29. [PMID: 33794735 PMCID: PMC8023248 DOI: 10.1080/19490976.2021.1902705] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/01/2021] [Accepted: 03/04/2021] [Indexed: 02/04/2023] Open
Abstract
South Asian (SA) Canadian immigrants have a higher risk of developing certain immune-mediated inflammatory diseases compared to non-migrant SAs. We sought to investigate the effect of migration on the gut metagenome and to identify microbiological associations between migration and conditions that may influence the development of immune-mediated inflammatory diseases. Metagenomic analysis of 58 first-generation (GEN1) SA immigrants and 38 unrelated Canadian born children-of-immigrants (GEN2) determined that the time lived in Canada was associated with continued changes in gut microbial communities. Migration of GEN1 to Canada early in life results in a gut community with similarities to GEN2 SA Canadians and non-SA North Americans. Conversely, GEN1 immigrants who arrived recently to Canada exhibited pronounced differences from GEN2, while displaying microbial similarities to a non-migrating SA cohort. Multivariate analysis identified that community composition was primarily influenced by high abundance taxa. Prevotella copri dominated in GEN1 and non-migrant SAs. Clostridia and functionally related Bacteroidia spp. replaced P. copri dominance over generations in Canada. Mutually exclusive Dialister species occurred at differing relative abundances over time and generations in Canada. This shift in species composition is accompanied by a change in genes associated with carbohydrate utilization and short-chain fatty acid production. Total energy derived from carbohydrates compared to protein consumption was significantly higher for GEN1 recent immigrants, which may influence the functional requirements of the gut community. This study demonstrates the associations between migration and the gut microbiome, which may be further associated with the altered risk of immune-mediated inflammatory diseases observed for SA Canadians.
Collapse
Affiliation(s)
- Julia K. Copeland
- Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, CA, Canada
| | - Gary Chao
- Department of Immunology, University of Toronto, Toronto, CA, Canada
| | - Shelley Vanderhout
- Nutrigenomix, Department of Nutritional Sciences, University of Toronto, Toronto, CA, Canada
| | - Erica Acton
- Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, CA, Canada
| | - Pauline W. Wang
- Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, CA, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, CA, Canada
| | - Eric I. Benchimol
- Department of Pediatrics, and School of Epidemiology and Public Health, University of Ottawa, Ottawa, CA, Canada
| | - Ahmed El-Sohemy
- Department of Nutritional Sciences, University of Toronto, Toronto, CA, Canada
| | - Ken Croitoru
- Department of Medicine, University of Toronto and Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital, Toronto, CA, Canada
| | | | - David S. Guttman
- Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, CA, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, CA, Canada
| | - the GEMINI Research Team
- Centre for the Analysis of Genome Evolution and Function, University of Toronto, Toronto, CA, Canada
- Department of Immunology, University of Toronto, Toronto, CA, Canada
- Nutrigenomix, Department of Nutritional Sciences, University of Toronto, Toronto, CA, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, CA, Canada
- Department of Pediatrics, and School of Epidemiology and Public Health, University of Ottawa, Ottawa, CA, Canada
- Department of Nutritional Sciences, University of Toronto, Toronto, CA, Canada
- Department of Medicine, University of Toronto and Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital, Toronto, CA, Canada
| |
Collapse
|
47
|
Sailwal M, Das AJ, Gazara RK, Dasgupta D, Bhaskar T, Hazra S, Ghosh D. Connecting the dots: Advances in modern metabolomics and its application in yeast system. Biotechnol Adv 2020; 44:107616. [DOI: 10.1016/j.biotechadv.2020.107616] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 08/15/2020] [Accepted: 08/17/2020] [Indexed: 12/15/2022]
|
48
|
Colby GA, Ruuskanen MO, St.Pierre KA, St.Louis VL, Poulain AJ, Aris-Brosou S. Warming Climate Is Reducing the Diversity of Dominant Microbes in the Largest High Arctic Lake. Front Microbiol 2020; 11:561194. [PMID: 33133035 PMCID: PMC7579425 DOI: 10.3389/fmicb.2020.561194] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 08/28/2020] [Indexed: 11/13/2022] Open
Abstract
Temperatures in the Arctic are expected to increase dramatically over the next century, and transform high latitude watersheds. However, little is known about how microbial communities and their underlying metabolic processes will be affected by these environmental changes in freshwater sedimentary systems. To address this knowledge gap, we analyzed sediments from Lake Hazen, NU Canada. Here, we exploit the spatial heterogeneity created by varying runoff regimes across the watershed of this uniquely large high-latitude lake to test how a transition from low to high runoff, used as one proxy for climate change, affects the community structure and functional potential of dominant microbes. Based on metagenomic analyses of lake sediments along these spatial gradients, we show that increasing runoff leads to a decrease in taxonomic and functional diversity of sediment microbes. Our findings are likely to apply to other, smaller, glacierized watersheds typical of polar or high latitude ecosystems; we can predict that such changes will have far reaching consequences on these ecosystems by affecting nutrient biogeochemical cycling, the direction and magnitude of which are yet to be determined.
Collapse
Affiliation(s)
- Graham A. Colby
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | | | - Kyra A. St.Pierre
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Vincent L. St.Louis
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | | | - Stéphane Aris-Brosou
- Department of Biology, University of Ottawa, Ottawa, ON, Canada
- Department of Mathematics and Statistics, University of Ottawa, Ottawa, ON, Canada
| |
Collapse
|
49
|
Donatti A, Canto AM, Godoi AB, da Rosa DC, Lopes-Cendes I. Circulating Metabolites as Potential Biomarkers for Neurological Disorders-Metabolites in Neurological Disorders. Metabolites 2020; 10:E389. [PMID: 33003305 PMCID: PMC7601919 DOI: 10.3390/metabo10100389] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 09/17/2020] [Accepted: 09/18/2020] [Indexed: 12/11/2022] Open
Abstract
There are, still, limitations to predicting the occurrence and prognosis of neurological disorders. Biomarkers are molecules that can change in different conditions, a feature that makes them potential tools to improve the diagnosis of disease, establish a prognosis, and monitor treatments. Metabolites can be used as biomarkers, and are small molecules derived from the metabolic process found in different biological media, such as tissue samples, cells, or biofluids. They can be identified using various strategies, targeted or untargeted experiments, and by different techniques, such as high-performance liquid chromatography, mass spectrometry, or nuclear magnetic resonance. In this review, we aim to discuss the current knowledge about metabolites as biomarkers for neurological disorders. We will present recent developments that show the need and the feasibility of identifying such biomarkers in different neurological disorders, as well as discuss relevant research findings in the field of metabolomics that are helping to unravel the mechanisms underlying neurological disorders. Although several relevant results have been reported in metabolomic studies in patients with neurological diseases, there is still a long way to go for the clinical use of metabolites as potential biomarkers in these disorders, and more research in the field is needed.
Collapse
Affiliation(s)
- Amanda Donatti
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Tessália Vieira de Camargo, 126 Cidade Universitária “Zeferino Vaz”, Campinas SP 13083-887, Brazil; (A.D.); (A.M.C.); (A.B.G.); (D.C.d.R.)
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas SP 13083-887, Brazil
| | - Amanda M. Canto
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Tessália Vieira de Camargo, 126 Cidade Universitária “Zeferino Vaz”, Campinas SP 13083-887, Brazil; (A.D.); (A.M.C.); (A.B.G.); (D.C.d.R.)
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas SP 13083-887, Brazil
| | - Alexandre B. Godoi
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Tessália Vieira de Camargo, 126 Cidade Universitária “Zeferino Vaz”, Campinas SP 13083-887, Brazil; (A.D.); (A.M.C.); (A.B.G.); (D.C.d.R.)
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas SP 13083-887, Brazil
| | - Douglas C. da Rosa
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Tessália Vieira de Camargo, 126 Cidade Universitária “Zeferino Vaz”, Campinas SP 13083-887, Brazil; (A.D.); (A.M.C.); (A.B.G.); (D.C.d.R.)
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas SP 13083-887, Brazil
| | - Iscia Lopes-Cendes
- Department of Medical Genetics and Genomic Medicine, School of Medical Sciences, University of Campinas (UNICAMP), Tessália Vieira de Camargo, 126 Cidade Universitária “Zeferino Vaz”, Campinas SP 13083-887, Brazil; (A.D.); (A.M.C.); (A.B.G.); (D.C.d.R.)
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas SP 13083-887, Brazil
| |
Collapse
|
50
|
Damale MG, Pathan SK, Patil RB, Sangshetti JN. Pharmacoinformatics approaches to identify potential hits against tetraacyldisaccharide 4'-kinase (LpxK) of Pseudomonas aeruginosa. RSC Adv 2020; 10:32856-32874. [PMID: 35516480 PMCID: PMC9056689 DOI: 10.1039/d0ra06675c] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 08/24/2020] [Indexed: 11/21/2022] Open
Abstract
Pseudomonas aeruginosa infection can cause pneumonia and urinary tract infection and the management of Pseudomonas aeruginosa infection is critical in multidrug resistance, hospital-acquired bacteremia and ventilator-associated pneumonia. The key enzymes of lipid A biosynthesis in Pseudomonas aeruginosa are promising drug targets. However, the enzyme tetraacyldisaccharide 4'-kinase (LpxK) has not been explored as a drug target so far. Several pharmacoinformatics tools such as comparative metabolic pathway analysis (Metacyc), data mining from a database of essential genes (DEG), homology modeling, molecular docking, pharmacophore based virtual screening, ADMET prediction and molecular dynamics simulation were used in identifying novel lead compounds against this target. The top virtual hits STOCK6S-33288, 43621, 39892, 37164 and 35740 may serve as the templates for the design and synthesis of potent LpxK inhibitors in the management of serious Pseudomonas aeruginosa infection.
Collapse
Affiliation(s)
- Manoj G Damale
- Y.B. Chavan College of Pharmacy Dr. Rafiq Zakaria Campus, Rauza Baugh Aurangabad MS 431001 India
- Srinath College of Pharmacy Aurangabad MS India
| | - Shahebaaz K Pathan
- Y.B. Chavan College of Pharmacy Dr. Rafiq Zakaria Campus, Rauza Baugh Aurangabad MS 431001 India
| | - Rajesh B Patil
- Sinhgad Technical Education Society's, Smt. Kashibai Navale College of Pharmacy Pune-Saswad Road, Kondhwa (Bk) Pune 411048 India
| | - Jaiprakash N Sangshetti
- Y.B. Chavan College of Pharmacy Dr. Rafiq Zakaria Campus, Rauza Baugh Aurangabad MS 431001 India
| |
Collapse
|