Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology

ClsC protein encoded by a stress-responsive operon in Escherichia coli functions as a trans-acting activator of RNase III

RNase III, an endoribonuclease that cleaves double-stranded RNAs (dsRNAs), significantly impacts Escherichia coli (E. coli) adaptation by regulating global RNA gene expression. YmdB from E. coli was characterized as a trans-acting regulator of RNase III. However, no protein encoded in E. coli has been characterized as an activator of RNase III. This study reports the discovery of ClsC protein, a phospholipase D (PLD) superfamily enzyme previously known as the third cardiolipin synthase (Cls) and a biofilm inhibitor in E. coli, as a novel RNase III activator. Overexpression of clsC in vivo stimulated the cleavage of RNase III-targeted lacZ fusions and antagonized the inhibition of RNase III by YmdB. Additional in vitro cleavage assays of RNase III-targeted RNAs using RNase III and ClsC confirmed this activity. Moreover, we identified multiple RNAs targeted by RNase III that are regulated dependently on cellular ClsC levels. Mechanistic investigations revealed that ClsC interacts with RNase III. Moreover, the isoleucine residue at the 466th position from the N-terminus of ClsC was identified as crucial for ClsC function. This study is the first to demonstrate that the ymdAB-clsC operon serves as an unexpected source for RNase III regulation in E. coli.

Advances in AI-based strategies and tools to facilitate natural product and drug development

Natural products and their derivatives have been important for treating diseases in humans, animals, and plants. However, discovering new structures from natural sources is still challenging. In recent years, artificial intelligence (AI) has greatly aided the discovery and development of natural products and drugs. AI facilitates to: connect genetic data to chemical structures or vice-versa, repurpose known natural products, predict metabolic pathways, and design and optimize metabolites biosynthesis. More recently, the emergence and improvement in neural networks such as deep learning and ensemble automated web based bioinformatics platforms have sped up the discovery process. Meanwhile, AI also improves the identification and structure elucidation of unknown compounds from raw data like mass spectrometry and nuclear magnetic resonance. This article reviews these AI-driven methods and tools, highlighting their practical applications and guide for efficient natural product discovery and drug development.

An intranuclear bacterial parasite of deep-sea mussels expresses apoptosis inhibitors acquired from its host

A limited number of bacteria are able to colonize the nuclei of eukaryotes. 'Candidatus Endonucleobacter' infects the nuclei of deep-sea mussels, where it replicates to ≥80,000 bacteria per nucleus and causes nuclei to swell to 50 times their original size. How these parasites are able to replicate and avoid apoptosis is not known. Dual RNA-sequencing transcriptomes of infected nuclei isolated using laser-capture microdissection revealed that 'Candidatus Endonucleobacter' does not obtain most of its nutrition from nuclear DNA or RNA. Instead, 'Candidatus Endonucleobacter' upregulates genes for importing and digesting sugars, lipids, amino acids and possibly mucin from its host. It likely prevents apoptosis of host cells by upregulating 7-13 inhibitors of apoptosis, proteins not previously seen in bacteria. Comparative phylogenetic analyses revealed that 'Ca. Endonucleobacter' acquired inhibitors of apoptosis through horizontal gene transfer from their hosts. Horizontal gene transfer from eukaryotes to bacteria is assumed to be rare, but may be more common than currently recognized.

A multi-omics insight on the interplay between iron deficiency and N forms in tomato

Introduction

Nitrogen (N) and iron (Fe) are involved in several biochemical processes in living organisms, and their limited bioavailability is a strong constraint for plant growth and yield. This work investigated the interplay between Fe and N nutritional pathways in tomato plants kept under N and Fe deficiency and then resupplied with Fe and N (as nitrate, ammonium, or urea) through a physiological, metabolomics and gene expression study.

Results

After 24 hours of Fe resupply, the Fe concentration in Fe-deficient roots was dependent on the applied N form (following the pattern: nitrate > urea > ammonium > Fe-deficient control), and whereas in leaves of urea treated plants the Fe concentration was lower in comparison to the other N forms. Untargeted metabolomics pointed out distinctive modulations of plant metabolism in a treatment-dependent manner. Overall, N-containing metabolites were affected by the treatments in both leaves and roots, while N form significantly shaped the phytohormone profile. Moreover, the simultaneous application of Fe with N to Fe-deficient plants elicited secondary metabolites' accumulation, such as phenylpropanoids, depending on the applied N form (mainly by urea, followed by nitrate and ammonium). After 4 hours of treatment, ammonium- and urea-treated roots showed a reduction of enzymatic activity of Fe(III)-chelate reductase (FCR), compared to nitrate or N-depleted plants (maintained in Fe deficiency, where FCR was maintained at high levels). The response of nitrate-treated plants leads to the improvement of Fe concentration in tomato roots and the increase of Fe(II) transporter (IRT1) gene expression in tomato roots.

Conclusions

Our results strengthen and improve the understanding about the interaction between N and Fe nutritional pathways, thinning the current knowledge gap.

Proteogenomic reconstruction of organ-specific metabolic networks in an environmental sentinel species, the amphipod Gammarus fossarum

Metabolic pathways are affected by the impacts of environmental contaminants underlying a large variability of toxic effects across different species. However, the systematic reconstruction of metabolic pathways remains limited in environmental sentinel species due to the lack of available genomic data in many taxa of animal diversity. In this study we used a multi-omics approach to reconstruct the most comprehensive map of metabolic pathways for a crustacean model in biomonitoring, the amphipod Gammarus fossarum in order to improve the knowledge of the metabolism of this sentinel species. We revisited the assembly of RNA-seq data by de novo approaches to reduce RNA contaminants and transcript redundancy. We also acquired extensive mass spectrometry shotgun proteomic data on several organs from a reference population of G. fossarum males and females to identify organ-specific metabolic profiles. The G. fossarum metabolic pathway reconstruction (available through the metabolic database GamfoCyc) was performed by adapting the genomic tool CycADS and we identified 377 pathways representing 7630 annotated enzymes, 2610 enzymatic reactions and the expression of 858 enzymes was experimentally validated by proteomics. To our knowledge, our analysis provides for the first time a systematic metabolic pathway reconstruction and the proteome profiles of these pathways at the organ level in this sentinel species. As an example, we show an elevated abundance in enzymes involved in ATP biosynthesis and fatty acid beta-oxidation indicative of the high-energy requirement of the gills, or the key anabolic and detoxification role of the hepatopancreatic caeca, as exemplified by the specific expression of the retinoid biosynthetic pathways and glutathione synthesis. In conclusion, the multi-omics data integration performed in this study provides new resources to investigate metabolic processes in crustacean amphipods and their role in mediating the effects of environmental contaminant exposures in sentinel species. SYNOPSIS: This study provide the first evidence that it is possible to combine multiple omics data to exhaustively describe the metabolic network of a model species in ecotoxicology, Gammarus fossarum, for which a reference genome is not yet available.

Longitudinal Transcriptomic, Proteomic, and Metabolomic Response of Citrus sinensis to Diaphorina citri Inoculation of Candidatus Liberibacter asiaticus

Huanglongbing (HLB) is a fatal citrus disease that is currently threatening citrus varieties worldwide. One putative causative agent, Candidatus Liberibacter asiaticus (CLas), is vectored by Diaphorina citri, known as the Asian citrus psyllid (ACP). Understanding the details of CLas infection in HLB disease has been hindered by its Candidatus nature and the inability to confidently detect it in diseased trees during the asymptomatic stage. To identify early changes in citrus metabolism in response to inoculation of CLas using its natural psyllid vector, leaves from Madam Vinous sweet orange (Citrus sinensis (L.) Osbeck) trees were exposed to CLas-positive ACP or CLas-negative ACP and longitudinally analyzed using transcriptomics (RNA sequencing), proteomics (liquid chromatography-tandem mass spectrometry; data available in Dryad: 10.25338/B83H1Z), and metabolomics (proton nuclear magnetic resonance). At 4 weeks postexposure (wpe) to psyllids, the initial HLB plant response was primarily to the ACP and, to a lesser extent, the presence or absence of CLas. Additionally, analysis of 4, 8, 12, and 16 wpe identified 17 genes and one protein as consistently differentially expressed between leaves exposed to CLas-positive ACP versus CLas-negative ACP. This study informs identification of early detection molecular targets and contributes to a broader understanding of vector-transmitted plant pathogen interactions.

Advancing environmental biotechnology with microbial community modeling rooted in functional 'omics

Emerging biotechnologies that solve pressing environmental and climate emergencies will require harnessing the vast functional diversity of the underlying microbiomes driving such engineered processes. Modeling is a critical aspect of process engineering that informs system design as well as aids diagnostic optimization of performance. 'Conventional' bioprocess models assume homogenous biomass within functional guilds and thus fail to predict emergent properties of diverse microbial physiologies, such as product specificity and community interactions. Yet, recent advances in functional 'omics-based approaches can provide a 'lens' through which we can probe and measure in situ ecophysiologies of environmental microbiomes. Here, we overview microbial community modeling approaches that incorporate functional 'omics data, which we posit can advance our ability to design and control new environmental biotechnologies going forward.

Insights into the differences related to the resistance mechanisms to the highly toxic fruit Hippomane mancinella (Malpighiales: Euphorbiaceae) between the larvae of the sister species Anastrepha acris and Anastrepha ludens (Diptera: Tephritidae) through comparative transcriptomics

The Manchineel, Hippomane mancinella ("Death Apple Tree") is one of the most toxic fruits worldwide and nevertheless is the host plant of the monophagous fruit fly species Anastrepha acris (Diptera: Tephritidae). Here we aimed at elucidating the detoxification mechanisms in larvae of A. acris reared on a diet enriched with the toxic fruit (6% lyophilizate) through comparative transcriptomics. We compared the performance of A. acris larvae with that of the sister species A. ludens, a highly polyphagous pest species that is unable to infest H. mancinella in nature. The transcriptional alterations in A. ludens were significantly greater than in A. acris. We mainly found two resistance mechanisms in both species: structural, activating cuticle protein biosynthesis (chitin-binding proteins likely reducing permeability to toxic compounds in the intestine), and metabolic, triggering biosynthesis of serine proteases and xenobiotic metabolism activation by glutathione-S-transferases and cytochrome P450 oxidoreductase. Some cuticle proteins and serine proteases were not orthologous between both species, suggesting that in A. acris, a structural resistance mechanism has been selected allowing specialization to the highly toxic host plant. Our results represent a nice example of how two phylogenetically close species diverged over recent evolutionary time related to resistance mechanisms to plant secondary metabolites.

Comparative genomics of a vertically transmitted thiotrophic bacterial ectosymbiont and its close free-living relative

Thiotrophic symbioses between sulphur-oxidizing bacteria and various unicellular and metazoan eukaryotes are widespread in reducing marine environments. The giant colonial ciliate Zoothamnium niveum, however, is the only host of thioautotrophic symbionts that has been cultivated along with its symbiont, the vertically transmitted ectosymbiont Candidatus Thiobius zoothamnicola (short Thiobius). Because theoretical predictions posit a smaller genome in vertically transmitted endosymbionts compared to free-living relatives, we investigated whether this is true also for an ectosymbiont. We used metagenomics to recover the high-quality draft genome of this bacterial symbiont. For comparison we have also sequenced a closely related free-living cultured but not formally described strain Milos ODIII6 (short ODIII6). We then performed comparative genomics to assess the functional capabilities at gene, metabolic pathway and trait level. 16S rRNA gene trees and average amino acid identity confirmed the close phylogenetic relationship of both bacteria. Indeed, Thiobius has about a third smaller genome than its free-living relative ODIII6, with reduced metabolic capabilities and fewer functional traits. The functional capabilities of Thiobius were a subset of those of the more versatile ODIII6, which possessed additional genes for oxygen, sulphur and hydrogen utilization and for the acquisition of phosphorus illustrating features that may be adaptive for the unstable environmental conditions at hydrothermal vents. In contrast, Thiobius possesses genes potentially enabling it to utilize lactate and acetate heterotrophically, compounds that may be provided as byproducts by the host. The present study illustrates the effect of strict host-dependence of a bacterial ectosymbiont on genome evolution and host adaptation.

Tumor-resident Lactobacillus iners confer chemoradiation resistance through lactate-induced metabolic rewiring

Tumor microbiota can produce active metabolites that affect cancer and immune cell signaling, metabolism, and proliferation. Here, we explore tumor and gut microbiome features that affect chemoradiation response in patients with cervical cancer using a combined approach of deep microbiome sequencing, targeted bacterial culture, and in vitro assays. We identify that an obligate L-lactate-producing lactic acid bacterium found in tumors, Lactobacillus iners, is associated with decreased survival in patients, induces chemotherapy and radiation resistance in cervical cancer cells, and leads to metabolic rewiring, or alterations in multiple metabolic pathways, in tumors. Genomically similar L-lactate-producing lactic acid bacteria commensal to other body sites are also significantly associated with survival in colorectal, lung, head and neck, and skin cancers. Our findings demonstrate that lactic acid bacteria in the tumor microenvironment can alter tumor metabolism and lactate signaling pathways, causing therapeutic resistance. Lactic acid bacteria could be promising therapeutic targets across cancer types.

Trichoderma spp.-mediated mitigation of heat, drought, and their combination on the Arabidopsis thaliana holobiont: a metabolomics and metabarcoding approach

Introduction

The use of substances to increase productivity and resource use efficiency is now essential to face the challenge of feeding the rising global population with the less environmental impact on the ecosystems. Trichoderma-based products have been used as biopesticides, to inhibit pathogenic microorganisms, and as biostimulants for crop growth, nutrient uptake promotion, and resistance to abiotic stresses.

Methods

In this work, plant metabolomics combined with roots and rhizosphere bacterial metabarcoding were exploited to inspect the performance of Trichoderma spp. biostimulants on Arabidopsis thaliana under drought, heat and their combination and its impact on plant holobiont.

Results and discussion

An overall modulation of N-containing compounds, phenylpropanoids, terpenes and hormones could be pointed out by metabolomics. Moreover, metabarcoding outlined an impact on alpha and beta-diversity with an abundance of Proteobacteria, Pseudomonadales, Burkholderiales, Enterobacteriales and Azospirillales. A holobiont approach was applied as an integrated analytical strategy to resolve the coordinated and complex dynamic interactions between the plant and its rhizosphere bacteria using Arabidopsis thaliana as a model host species.

Antioxidant Green Factories: Toward Sustainable Production of Vitamin E in Plant In Vitro Cultures

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.

CuGenDBv2: an updated database for cucurbit genomics

The Cucurbitaceae (cucurbit) family consists of about 1,000 species in 95 genera, including many economically important and popular fruit and vegetable crops. During the past several years, reference genomes have been generated for >20 cucurbit species, and variome and transcriptome profiling data have been rapidly accumulated for cucurbits. To efficiently mine, analyze and disseminate these large-scale datasets, we have developed an updated version of Cucurbit Genomics Database. The updated database, CuGenDBv2 (http://cucurbitgenomics.org/v2), currently hosts 34 reference genomes from 27 cucurbit species/subspecies belonging to 10 different genera. Protein-coding genes from these genomes have been comprehensively annotated by comparing their protein sequences to various public protein and domain databases. A novel 'Genotype' module has been implemented to facilitate mining and analysis of the functionally annotated variome data including SNPs and small indels from large-scale genome sequencing projects. An updated 'Expression' module has been developed to provide a comprehensive gene expression atlas for cucurbits. Furthermore, synteny blocks between any two and within each of the 34 genomes, representing a total of 595 pair-wise genome comparisons, have been identified and can be explored and visualized in the database.

Revealing the Phenotypic and Genomic Background for PHA Production from Rapeseed-Biodiesel Crude Glycerol Using Photobacterium ganghwense C2.2

Polyhydroxyalkanoates (PHA) are promising biodegradable and biocompatible bioplastics, and extensive knowledge of the employed bacterial strain's metabolic capabilities is necessary in choosing economically feasible production conditions. This study aimed to create an in-depth view of the utilization of Photobacterium ganghwense C2.2 for PHA production by linking a wide array of characterization methods: metabolic pathway annotation from the strain's complete genome, high-throughput phenotypic tests, and biomass analyses through plate-based assays and flask and bioreactor cultivations. We confirmed, in PHA production conditions, urea catabolization, fatty acid degradation and synthesis, and high pH variation and osmotic stress tolerance. With urea as a nitrogen source, pure and rapeseed-biodiesel crude glycerol were analyzed comparatively as carbon sources for fermentation at 20 °C. Flask cultivations yielded 2.2 g/L and 2 g/L PHA at 120 h, respectively, with molecular weights of 428,629 g/mol and 81,515 g/mol. Bioreactor batch cultivation doubled biomass accumulation (10 g/L and 13.2 g/L) in 48 h, with a PHA productivity of 0.133 g/(L·h) and 0.05 g/(L·h). Thus, phenotypic and genomic analyses determined the successful use of Photobacterium ganghwense C2.2 for PHA production using urea and crude glycerol and 20 g/L NaCl, without pH adjustment, providing the basis for a viable fermentation process.

Biochemical Insights into the Ability of Lemna minor L. Extract to Counteract Copper Toxicity in Maize

Metal trace elements (MTE) can damage crops if present in excessive amounts in the environment. This research investigated the effect of a plant extract of an aquatic species, Lemna minor L. (duckweed) (LE), on the ability of maize to cope with copper (Cu) toxicity. LE reversed the effects of Cu²⁺ on photosynthetic activity (Pn), evapotranspiration (E), stomatal conductance (gs), sub-stomatal CO₂ concentration (Ci) and biomass which did not differ from the untreated controls. LE did not regulate the amount of copper in maize leaves, but compared to Cu-treated samples, the extract decreased the hydrogen peroxide (H₂O₂; -26% on average) and malondialdehyde (MDA; -47% on average) content, regardless of the dosage applied. Furthermore, the activity of antioxidant enzymes superoxide dismutase (SOD), ascorbate peroxidase (APX) and catalase (CAT) was significantly increased by LE compared to samples treated with Cu alone. Untargeted metabolomic profiling revealed that LE activated maize secondary metabolism, eliciting the content of non-enzymatic antioxidants (flavonoids, glutathione and glutathione-related compounds, tocopherols and tocotrienols) and modulating plant stress-related hormones (brassinosteroids and ABA derivatives). The results of this study are promising and pave the way for using duckweed as a biostimulant to trigger beneficial effects in maize and increase its resistance to MTEs.

Identification and Characterization of a Novel Species of Genus Akkermansia with Metabolic Health Effects in a Diet-Induced Obesity Mouse Model

Akkermansia muciniphila is a well-known bacterium with the ability to degrade mucin. This metabolic capability is believed to play an important role in the colonization of this bacterium in the gut. In this study, we report the identification and characterization of a novel Akkermansia sp. DSM 33459 isolated from human feces of a healthy donor. Phylogenetic analysis based on the genome-wide average nucleotide identity indicated that the Akkermansia sp. DSM 33459 has only 87.5% similarity with the type strain A. muciniphila ATCC BAA-835. Akkermansia sp. DSM 33459 showed significant differences in its fatty acid profile and carbon utilization as compared to the type strain. The Akkermansia sp. DSM 33459 strain was tested in a preclinical obesity model to determine its effect on metabolic markers. Akkermansia sp. DSM 33459 showed significant improvement in body weight, total fat weight, and resistin and insulin levels. Interestingly, these effects were more pronounced with the live form as compared to a pasteurized form of the strain. The strain showed production of agmatine, suggesting a potential novel mechanism for supporting metabolic and cognitive health. Based on its phenotypic features and phylogenetic position, it is proposed that this isolate represents a novel species in the genus Akkermansia and a promising therapeutic candidate for the management of metabolic diseases.

Novel thermophilic polyhydroxyalkanoates producing strain Aneurinibacillus thermoaerophilus CCM 8960

Aneurinibacillus thermoaerophilus CCM 8960 is a thermophilic bacterium isolated from compost in Brno. The bacterium accumulates polyhydroxyalkanoates (PHAs), a biodegradable and renewable alternative to petrochemical polymers. The bacterium reveals several features that make it a very interesting candidate for the industrial production of PHA. At first, due to its thermophilic character, the bacterium can be utilized in agreement with the concept of next-generation industrial biotechnology (NGIB), which relies on extremophiles. Second, the bacterium is capable of producing PHA copolymers containing a very high portion of 4-hydroxybutyrate (4HB). Such materials possess unique properties and can be advantageously used in multiple applications, including but not limited to medicine and healthcare. Therefore, this work focuses on the in-depth characterization of A. thermoaerophilus CCM 8960. In particular, we sequenced and assembled the genome of the bacterium and identified its most important genetic features, such as the presence of plasmids, prophages, CRISPR arrays, antibiotic-resistant genes, and restriction-modification (R-M) systems, which might be crucial for the development of genome editing tools. Furthermore, we focused on genes directly involved in PHA metabolism. We also experimentally studied the kinetics of glycerol and 1,4-butanediol (1,4BD) utilization as well as biomass growth and PHA production during cultivation. Based on these data, we constructed a metabolic model to reveal metabolic fluxes and nodes of glycerol and 1,4BD concerning their incorporation into the poly(3-hydroxybutyrate-co-4-hydroxybutyrate (P(3HB-co-4HB)) structure. KEY POINTS: • Aneurinibacillus sp. H1 was identified as Aneurinibacillus thermoaerophilus. • PHA metabolism pathway with associated genes was presented. • Unique monomer composition of produced PHAs was reported.

DeepRF: A deep learning method for predicting metabolic pathways in organisms based on annotated genomes

The rapid increase of metabolomics has led to an increasing focus on metabolic pathway modeling and reconstruction. In particular, reconstructing an organism's metabolic network based on its genome sequence is a key challenge in systems biology. The method used to address this problem predicts the presence or absence of metabolic pathways from known pathways in a reference database. However, this method is based on manual metabolic pathway construction and cannot be used for large genome sequencing data. To address such problems, we apply a supervised machine learning approach consisting of deep neural networks to learn feature representations of metabolic pathways and feed these representations into random forests to predict metabolic pathways. The supervised learning model, DeepRF, predicts all known and unknown metabolic pathways in an organism. Evaluation of DeepRF on over 318,016 instances shows that the model can predict metabolic pathways with high-performance metrics accuracy (>97%), recall (>95%), and precision (>99%). Comparing DeepRF with other methods in the literature shows that DeepRF produces more reliable results than other methods.

Nitrogen use efficiency, rhizosphere bacterial community, and root metabolome reprogramming due to maize seed treatment with microbial biostimulants

Seed inoculation with beneficial microorganisms has gained importance as it has been proven to show biostimulant activity in plants, especially in terms of abiotic/biotic stress tolerance and plant growth promotion, representing a sustainable way to ensure yield stability under low input sustainable agriculture. Nevertheless, limited knowledge is available concerning the molecular and physiological processes underlying the root-inoculant symbiosis or plant response at the root system level. Our work aimed to integrate the interrelationship between agronomic traits, rhizosphere microbial population and metabolic processes in roots, following seed treatment with either arbuscular mycorrhizal fungi (AMF) or Plant Growth-Promoting Rhizobacteria (PGPR). To this aim, maize was grown under open field conditions with either optimal or reduced nitrogen availability. Both seed treatments increased nitrogen uptake efficiency under reduced nitrogen supply revealed some microbial community changes among treatments at root microbiome level and limited yield increases, while significant changes could be observed at metabolome level. Amino acid, lipid, flavone, lignan, and phenylpropanoid concentrations were mostly modulated. Integrative analysis of multi-omics datasets (Multiple Co-Inertia Analysis) highlighted a strong correlation between the metagenomics and the untargeted metabolomics datasets, suggesting a coordinate modulation of root physiological traits.

Complete de novo assembly of Wolbachia endosymbiont of Diaphorina citri Kuwayama (Hemiptera: Liviidae) using long-read genome sequencing

Wolbachia, a gram-negative \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathrm{\alpha }$$\end{document}α-proteobacterium, is an endosymbiont found in some arthropods and nematodes. Diaphorina citri Kuwayama, the vector of ‘Candidatus Liberibacter asiaticus’ (CLas), are naturally infected with a strain of Wolbachia (wDi), which has been shown to colocalize with the bacteria pathogens CLas, the pathogen associated with huanglongbing (HLB) disease of citrus. The relationship between wDi and CLas is poorly understood in part because the complete genome of wDi has not been available. Using high-quality long-read PacBio circular consensus sequences, we present the largest complete circular wDi genome among supergroup-B members. The assembled circular chromosome is 1.52 megabases with 95.7% genome completeness with contamination of 1.45%, as assessed by checkM. We identified Insertion Sequences (ISs) and prophage genes scattered throughout the genomes. The proteins were annotated using Pfam, eggNOG, and COG that assigned unique domains and functions. The wDi genome was compared with previously sequenced Wolbachia genomes using pangenome and phylogenetic analyses. The availability of a complete circular chromosome of wDi will facilitate understanding of its role within the insect vector, which may assist in developing tools for disease management. This information also provides a baseline for understanding phylogenetic relationships among Wolbachia of other insect vectors.

Evolutionarily recent dual obligatory symbiosis among adelgids indicates a transition between fungus- and insect-associated lifestyles

Adelgids (Insecta: Hemiptera: Adelgidae) form a small group of insects but harbor a surprisingly diverse set of bacteriocyte-associated endosymbionts, which suggest multiple replacement and acquisition of symbionts over evolutionary time. Specific pairs of symbionts have been associated with adelgid lineages specialized on different secondary host conifers. Using a metagenomic approach, we investigated the symbiosis of the Adelges laricis/Adelges tardus species complex containing betaproteobacterial ("Candidatus Vallotia tarda") and gammaproteobacterial ("Candidatus Profftia tarda") symbionts. Genomic characteristics and metabolic pathway reconstructions revealed that Vallotia and Profftia are evolutionary young endosymbionts, which complement each other's role in essential amino acid production. Phylogenomic analyses and a high level of genomic synteny indicate an origin of the betaproteobacterial symbiont from endosymbionts of Rhizopus fungi. This evolutionary transition was accompanied with substantial loss of functions related to transcription regulation, secondary metabolite production, bacterial defense mechanisms, host infection, and manipulation. The transition from fungus to insect endosymbionts extends our current framework about evolutionary trajectories of host-associated microbes.

The metabolic core of the prokaryotic community from deep-sea sediments of the southern Gulf of Mexico shows different functional signatures between the continental slope and abyssal plain

Marine sediments harbor an outstanding level of microbial diversity supporting diverse metabolic activities. Sediments in the Gulf of Mexico (GoM) are subjected to anthropic stressors including oil pollution with potential effects on microbial community structure and function that impact biogeochemical cycling. We used metagenomic analyses to provide significant insight into the potential metabolic capacity of the microbial community in Southern GoM deep sediments. We identified genes for hydrocarbon, nitrogen and sulfur metabolism mostly affiliated with Alpha and Betaproteobacteria, Acidobacteria, Chloroflexi and Firmicutes, in relation to the use of alternative carbon and energy sources to thrive under limiting growth conditions, and metabolic strategies to cope with environmental stressors. In addition, results show amino acids metabolism could be associated with sulfur metabolism carried out by Acidobacteria, Chloroflexi and Firmicutes, and may play a crucial role as a central carbon source to favor bacterial growth. We identified the tricarboxylic acid cycle (TCA) and aspartate, glutamate, glyoxylate and leucine degradation pathways, as part of the core carbon metabolism across samples. Further, microbial communities from the continental slope and abyssal plain show differential metabolic capacities to cope with environmental stressors such as oxidative stress and carbon limiting growth conditions, respectively. This research combined taxonomic and functional information of the microbial community from Southern GoM sediments to provide fundamental knowledge that links the prokaryotic structure to its potential function and which can be used as a baseline for future studies to model microbial community responses to environmental perturbations, as well as to develop more accurate mitigation and conservation strategies.

On the optimality of the enzyme-substrate relationship in bacteria

Much recent progress has been made to understand the impact of proteome allocation on bacterial growth; much less is known about the relationship between the abundances of the enzymes and their substrates, which jointly determine metabolic fluxes. Here, we report a correlation between the concentrations of enzymes and their substrates in Escherichia coli. We suggest this relationship to be a consequence of optimal resource allocation, subject to an overall constraint on the biomass density: For a cellular reaction network composed of effectively irreversible reactions, maximal reaction flux is achieved when the dry mass allocated to each substrate is equal to the dry mass of the unsaturated (or “free”) enzymes waiting to consume it. Calculations based on this optimality principle successfully predict the quantitative relationship between the observed enzyme and metabolite abundances, parameterized only by molecular masses and enzyme–substrate dissociation constants (K_m). The corresponding organizing principle provides a fundamental rationale for cellular investment into different types of molecules, which may aid in the design of more efficient synthetic cellular systems.

This study shows that in E. coli, the cellular mass of each metabolite approximately equals the combined mass of the free enzymes waiting to consume it; this simple relationship arises from the optimal utilization of cellular dry mass, and quantitatively describes available experimental data.

Promoter Architecture Differences among Alphaproteobacteria and Other Bacterial Taxa

Much of our knowledge of bacterial transcription initiation has been derived from studying the promoters of Escherichia coli and Bacillus subtilis. Given the expansive diversity across the bacterial phylogeny, it is unclear how much of this knowledge can be applied to other organisms. Here, we report on bioinformatic analyses of promoter sequences of the primary σ factor (σ70) by leveraging publicly available transcription start site (TSS) sequencing data sets for nine bacterial species spanning five phyla. This analysis identifies previously unreported differences in the -35 and -10 elements of σ70-dependent promoters in several groups of bacteria. We found that Actinobacteria and Betaproteobacteria σ70-dependent promoters lack the TTG triad in their -35 element, which is predicted to be conserved across the bacterial phyla. In addition, the majority of the Alphaproteobacteria σ70-dependent promoters analyzed lacked the thymine at position -7 that is highly conserved in other phyla. Bioinformatic examination of the Alphaproteobacteria σ70-dependent promoters identifies a significant overrepresentation of essential genes and ones encoding proteins with common cellular functions downstream of promoters containing an A, C, or G at position -7. We propose that transcription of many σ70-dependent promoters in Alphaproteobacteria depends on the transcription factor CarD, which is an essential protein in several members of this phylum. Our analysis expands the knowledge of promoter architecture across the bacterial phylogeny and provides new information that can be used to engineer bacteria for use in medical, environmental, agricultural, and biotechnological processes. IMPORTANCE Transcription of DNA to RNA by RNA polymerase is essential for cells to grow, develop, and respond to stress. Understanding the process and control of transcription is important for health, disease, the environment, and biotechnology. Decades of research on a few bacteria have identified promoter DNA sequences that are recognized by the σ subunit of RNA polymerase. We used bioinformatic analyses to reveal previously unreported differences in promoter DNA sequences across the bacterial phylogeny. We found that many Actinobacteria and Betaproteobacteria promoters lack a sequence in their -35 DNA recognition element that was previously assumed to be conserved and that Alphaproteobacteria lack a thymine residue at position -7, also previously assumed to be conserved. Our work reports important new information about bacterial transcription, illustrates the benefits of studying bacteria across the phylogenetic tree, and proposes new lines of future investigation.

Systems biology for crop improvement

In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a result, full insight could not be gained on the molecular basis of complex traits and biological networks. A systems biology approach involving integration of multiple omics data, modeling, and prediction of the cellular functions is required to understand the flow of biological information that underlies complex traits. In this context, systems biology with multiomics data integration is crucial and allows a holistic understanding of the dynamic system with the different levels of biological organization interacting with external environment for a phenotypic expression. Here, we present recent progress made in the area of various omics studies-integrative and systems biology approaches with a special focus on application to crop improvement. We have also discussed the challenges and opportunities in multiomics data integration, modeling, and understanding of the biology of complex traits underpinning yield and stress tolerance in major cereals and legumes.

A Novel Freshwater to Marine Evolutionary Transition Revealed within Methylophilaceae Bacteria from the Arctic Ocean

Bacteria inhabiting polar oceans, particularly the Arctic Ocean, are less studied than those at lower latitudes. Discovering bacterial adaptations to Arctic Ocean conditions is essential for understanding responses to the accelerated environmental changes occurring in the North. The Methylophilaceae are emerging as a model for investigating the genomic basis of habitat adaptation, because related lineages are widely distributed across both freshwater and marine ecosystems. Here, we investigated Methylophilaceae diversity in the salinity-stratified surface waters of the Canada Basin, Arctic Ocean. In addition to a diversity of marine OM43 lineages, we report on the genomic characteristics and evolution of a previously undescribed Methylophilaceae clade (BS01) common to polar surface waters yet related to freshwater sediment Methylotenera species. BS01 is restricted to the lower-salinity surface waters, while OM43 is found throughout the halocline. An acidic proteome supports a marine lifestyle for BS01, but gene content shows increased metabolic versatility compared to OM43 and evidence for ongoing genome-streamlining. Phylogenetic reconstruction shows that BS01 colonized the pelagic ocean independently of OM43 via convergent evolution. Salinity adaptation and differences in one-carbon and nitrogen metabolism may play a role in niche differentiation between BS01 and OM43. In particular, urea utilization by BS01 is predicted to provide an ecological advantage over OM43 given the limited amount of inorganic nitrogen in the Canada Basin. These observations provide further evidence that the Arctic Ocean is inhabited by distinct bacterial groups and that at least one group (BS01) evolved via a freshwater to marine environmental transition.

A multi-objective hybrid machine learning approach-based optimization for enhanced biomass and bioactive phycobiliproteins production in Nostoc sp. CCC-403

The cyanobacterial phycobiliproteins (PBPs) are an important natural colorant for nutraceutical industries. Here, a multi-objective hybrid machine learning-based optimization approach was used for enhanced cell biomass and PBPs production simultaneously in Nostoc sp. CCC-403. A central composite design (CCD) was employed to design an experimental setup for four input parameters, including three BG-11 medium components and pH. We achieved a 61.76% increase in total PBPs production and an almost 90% increase in cell biomass by our prediction model. We also established a test genome-scale metabolic network (GSMN) for Nostoc sp. and identified potential metabolic fluxes contributing to PBPs enhanced production. This study highlights the advantage of the hybrid machine learning approach and GSMN to achieve optimization for more than one objective and serves as the foundation for future efforts to convert cyanobacteria as an economically viable source for biofuels and natural products.

Bacterial Cellulose Retains Robustness but Its Synthesis Declines After Exposure to a Mars-like Environment Simulated Outside the International Space Station

Cellulose is a widespread macromolecule in terrestrial environments and a major architectural component of microbial biofilm. Therefore, cellulose might be considered a biosignature that indicates the presence of microbial life. We present, for the first time, characteristics of bacterial cellulose after long-term spaceflight and exposure to simuled Mars-like stressors. The pristine cellulose-based pellicle membranes from a kombucha microbial community (KMC) were exposed outside the International Space Station, and after their return to Earth, the samples were reactivated and cultured for 2.5 years to discern whether the KMC could be restored. Analyses of cellulose polymer integrity and mechanical properties of cellulose-based pellicle films, as well as the cellulose biosynthesis-related genes' structure and expression, were performed. We observed that (i) the cellulose polymer integrity was not significantly changed under Mars-like conditions; (ii) de novo cellulose production was 1.5 times decreased in exposed KMC samples; (iii) the dry cellulose yield from the reisolated Komagataeibacter oboediens was 1.7 times lower than by wild type; (iv) there was no significant change in mechanical properties of the de novo synthesized cellulose-based pellicles produced by the exposed KMCs and K. oboediens; and (v) the gene, encoding biosynthesis of cellulose (bcsA) of the K. oboediens, was downregulated, and no topological change or mutation was observed in any of the bcs operon genes, indicating that the decreased cellulose production by the space-exposed samples was probably due to epigenetic regulation. Our results suggest that the cellulose-based pellicle could be a good material with which to protect microbial communities during space journeys, and the cellulose produced by KMC members could be suitable in the fabrication of consumer goods for extraterrestrial locations.

The extent of carbapenemase-encoding genes in public genome sequences

Genome sequences provide information on the genetic elements present in an organism, and currently there are databases containing hundreds of thousands of bacterial genome sequences. These repositories allow for mining patterns concerning antibiotic resistance gene occurrence in both pathogenic and non-pathogenic bacteria in e.g. natural or animal environments, and link these to relevant metadata such as bacterial host species, country and year of isolation, and co-occurrence with other resistance genes. In addition, the advances in the prediction of mobile genetic elements, and discerning chromosomal from plasmid DNA, broadens our view on the mechanism mediating dissemination. In this study we utilize the vast amount of data in the public database PATRIC to investigate the dissemination of carbapenemase-encoding genes (CEGs), the emergence and spread of which is considered a grave public health concern. Based on publicly available genome sequences from PATRIC and manually curated CEG sequences from the beta lactam database, we found 7,964 bacterial genomes, belonging to at least 70 distinct species, that carry in total 9,892 CEGs, amongst which bla _NDM, bla _OXA, bla _VIM, bla _IMP and bla _KPC. We were able to distinguish between chromosomally located resistance genes (4,137; 42%) and plasmid-located resistance genes (5,753; 58%). We found that a large proportion of the identified CEGs were identical, i.e. displayed 100% nucleotide similarity in multiple bacterial species (8,361 out of 9,892 genes; 85%). For example, the New Delhi metallo-beta-lactamase NDM-1 was found in 42 distinct bacterial species, and present in seven different environments. Our data show the extent of carbapenem-resistance far beyond the canonical species Acetinobacter baumannii, Klebsiella pneumoniae or Pseudomonas aeruginosa. These types of data complement previous systematic reviews, in which carbapenem-resistant Enterobacteriaceae were found in wildlife, livestock and companion animals. Considering the widespread distribution of CEGs, we see a need for comprehensive surveillance and transmission studies covering more host species and environments, akin to previous extensive surveys that focused on extended spectrum beta-lactamases. This may help to fully appreciate the spread of CEGs and improve the understanding of mechanisms underlying transmission, which could lead to interventions minimizing transmission to humans.

Heterozygous, Polyploid, Giant Bacterium, Achromatium, Possesses an Identical Functional Inventory Worldwide across Drastically Different Ecosystems

Achromatium is large, hyperpolyploid and the only known heterozygous bacterium. Single cells contain approximately 300 different chromosomes with allelic diversity far exceeding that typically harbored by single bacteria genera. Surveying all publicly available sediment sequence archives, we show that Achromatium is common worldwide, spanning temperature, salinity, pH, and depth ranges normally resulting in bacterial speciation. Although saline and freshwater Achromatium spp. appear phylogenetically separated, the genus Achromatium contains a globally identical, complete functional inventory regardless of habitat. Achromatium spp. cells from differing ecosystems (e.g., from freshwater to saline) are, unexpectedly, equally functionally equipped but differ in gene expression patterns by transcribing only relevant genes. We suggest that environmental adaptation occurs by increasing the copy number of relevant genes across the cell's hundreds of chromosomes, without losing irrelevant ones, thus maintaining the ability to survive in any ecosystem type. The functional versatility of Achromatium and its genomic features reveal alternative genetic and evolutionary mechanisms, expanding our understanding of the role and evolution of polyploidy in bacteria while challenging the bacterial species concept and drivers of bacterial speciation.

Complete genome sequence of Photobacterium ganghwense C2.2: A new polyhydroxyalkanoate production candidate

Polyhydroxyalkanoates (PHAs) are biodegradable bioplastics that can be manufactured sustainably and represent a promising green alternative to petrochemical-based plastics. Here, we describe the complete genome of a new marine PHA-producing bacterium-Photobacterium ganghwense (strain C2.2), which we have isolated from the Black Sea seashore. This new isolate is psychrotolerant and accumulates PHA when glycerol is provided as the main carbon source. Transmission electron microscopy, specific staining with Nile Red visualized via epifluorescence microscopy and gas chromatography analysis confirmed the accumulation of PHA. This is the only PHA-producing Photobacterium for which we now have a complete genome sequence, allowing us to investigate the pathways for PHA production and other secondary metabolite synthesis pathways. The de novo assembly genome, obtained using open-source tools, comprises two chromosomes (3.5, 2 Mbp) and a megaplasmid (202 kbp). We identify the entire PHA synthesis gene cluster that encodes a class I PHA synthase, a phasin, a 3-ketothiolase, and an acetoacetyl-CoA reductase. No conventional PHA depolymerase was identified in strain C2.2, but a putative lipase with extracellular amorphous PHA depolymerase activity was annotated, suggesting that C2.2 is unable to degrade intracellular PHA. A complete pathway for the conversion of glycerol to acetyl-CoA was annotated, in accordance with its ability to convert glycerol to PHA. Several secondary metabolite biosynthetic gene clusters and a low number of genes involved in antibiotic resistance and virulence were also identified, indicating the strain's suitability for biotechnological applications.

Foliar Application of Different Vegetal-Derived Protein Hydrolysates Distinctively Modulates Tomato Root Development and Metabolism

Despite the scientific evidence supporting their biostimulant activity, the molecular mechanism(s) underlying the activity of protein hydrolysates (PHs) and the specificity among different products are still poorly explored. This work tested five different protein hydrolysates, produced from different plant sources using the same enzymatic approach, for their ability to promote rooting in tomato cuttings following quick dipping. Provided that all the different PHs increased root length (45–93%) and some of them increased root number (37–56%), untargeted metabolomics followed by multivariate statistics and pathway analysis were used to unravel the molecular processes at the basis of the biostimulant activity. Distinct metabolomic signatures could be found in roots following the PHs treatments. In general, PHs shaped the phytohormone profile, modulating the complex interaction between cytokinins and auxins, an interplay playing a pivotal role in root development, and triggered a down accumulation of brassinosteroids. Concerning secondary metabolism, PHs induced the accumulation of aliphatic glucosinolates, alkaloids, and phenylpropanoids, potentially eliciting crop resilience to stress conditions. Here, we confirm that PHs may have a hormone-like activity, and that their application can modulate plant growth, likely interfering with signaling processes. Noteworthy, the heterogenicity of the botanical origin supported the distinctive and peculiar metabolomic responses we observed across the products tested. While supporting their biostimulant activity, these findings suggest that a generalized crop response to PHs cannot be defined and that specific effects are rather to be investigated.

Impact of Zero-Valent Iron on Freshwater Bacterioplankton Metabolism as Predicted from 16S rRNA Gene Sequence Libraries

The application of zero-valent iron particles (ZVI) for the treatment of heavily polluted environment and its biological effects have been studied for at least two decades. Still, information on the impact on bacterial metabolic pathways is lacking. This study describes the effect of microscale and nanoscale ZVI (mZVI and nZVI) on the abundance of different metabolic pathways in freshwater bacterial communities. The metabolic pathways were inferred from metabolism modelling based on 16S rRNA gene sequence data using paprica pipeline. The nZVI changed the abundance of numerous metabolic pathways compared to a less influencing mZVI. We identified the 50 most affected pathways, where 31 were related to degradation, 17 to biosynthesis, and 2 to detoxification. The linkage between pathways was two times higher in nZVI samples compared to mZVI, and was specifically higher considering the arsenate detoxification II pathway. Limnohabitans and Roseiflexus were linked to the same pathways in both nZVI and mZVI. The prediction of metabolic pathways increases our knowledge of the impacts of nZVI and mZVI on freshwater bacterioplankton.

Concealed metabolic reprogramming induced by different herbicides in tomato

Herbicide application is a common procedure in agriculture, whose potentially adverse effects are assessed mainly with respect to weeds or in terms of residues and environmental impact. However, recent evidence has highlighted possible effects of pesticide treatments on plant metabolism, with potential implications for fruit quality. Therefore, the goal of this study was to investigate the impact of four different herbicides on the metabolic processes in industrial tomato plants. To this aim, plants were treated either with the selective herbicides metribuzin and rimsulfuron or with the non-selective herbicides glyphosate and pelargonic acid. Thereafter, leaves were analyzed using a metabolomics approach, and 247 differential compounds were selected by multivariate statistics and used to examine the changes at the molecular level. Data interpretation via the PlantCyc Pathway Tool revealed that the tested herbicides induced distinctive responses to the treatments, with the phytohormone profile (gibberellins and jasmonates) and secondary metabolism (including stress-related compounds, such as phenylpropanoids and glucosinolates) showing the largest modulation. Surprisingly, such metabolic reprogramming also affected several aspects of the fruits even though the herbicides were applied several weeks before, thus opening the possibility of effects on food quality. To date, these hidden effects have been largely underestimated even though they deserve to be carefully considered since they may affect the qualitative and quantitative traits of the yield.

Pathway Tools Visualization of Organism-Scale Metabolic Networks

Metabolomics, synthetic biology, and microbiome research demand information about organism-scale metabolic networks. The convergence of genome sequencing and computational inference of metabolic networks has enabled great progress toward satisfying that demand by generating metabolic reconstructions from the genomes of thousands of sequenced organisms. Visualization of whole metabolic networks is critical for aiding researchers in understanding, analyzing, and exploiting those reconstructions. We have developed bioinformatics software tools that automatically generate a full metabolic-network diagram for an organism, and that enable searching and analyses of the network. The software generates metabolic-network diagrams for unicellular organisms, for multi-cellular organisms, and for pan-genomes and organism communities. Search tools enable users to find genes, metabolites, enzymes, reactions, and pathways within a diagram. The diagrams are zoomable to enable researchers to study local neighborhoods in detail and to see the big picture. The diagrams also serve as tools for comparison of metabolic networks and for interpreting high-throughput datasets, including transcriptomics, metabolomics, and reaction fluxes computed by metabolic models. These data can be overlaid on the metabolic charts to produce animated zoomable displays of metabolic flux and metabolite abundance. The BioCyc.org website contains whole-network diagrams for more than 18,000 sequenced organisms. The ready availability of organism-specific metabolic network diagrams and associated tools for almost any sequenced organism are useful for researchers working to better understand the metabolism of their organism and to interpret high-throughput datasets in a metabolic context.

A deep learning architecture for metabolic pathway prediction

MOTIVATION

Understanding the mechanisms and structural mappings between molecules and pathway classes are critical for design of reaction predictors for synthesizing new molecules. This article studies the problem of prediction of classes of metabolic pathways (series of chemical reactions occurring within a cell) in which a given biochemical compound participates. We apply a hybrid machine learning approach consisting of graph convolutional networks used to extract molecular shape features as input to a random forest classifier. In contrast to previously applied machine learning methods for this problem, our framework automatically extracts relevant shape features directly from input SMILES representations, which are atom-bond specifications of chemical structures composing the molecules.

RESULTS

Our method is capable of correctly predicting the respective metabolic pathway class of 95.16% of tested compounds, whereas competing methods only achieve an accuracy of 84.92% or less. Furthermore, our framework extends to the task of classification of compounds having mixed membership in multiple pathway classes. Our prediction accuracy for this multi-label task is 97.61%. We analyze the relative importance of various global physicochemical features to the pathway class prediction problem and show that simple linear/logistic regression models can predict the values of these global features from the shape features extracted using our framework.

AVAILABILITY AND IMPLEMENTATION

https://github.com/baranwa2/MetabolicPathwayPrediction.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular basis of rootstock-related tolerance to water deficit in Vitis vinifera L. cv. Sangiovese: A physiological and metabolomic combined approach

The rootstock M4 (V. vinifera × V. berlandieri) × V. berlandieri cv. Resseguier n.1) is a recent selection reported to confer improved drought tolerance to grafted V. vinifera scions, a very desired feature in the era of global warming. Therefore, a short-term study was performed on a batch of 12 potted cv. Sangiovese vines grafted either on M4 or on the drought susceptible SO4 rootstock. Ecophysiological assessments as whole canopy net CO₂ exchange rate (NCER), transpiration (T_c), and pre-dawn leaf water potential (Ψ_pd) and UHPLC-ESI/QTOF-MS metabolomics were then used to investigate the different vine responses during water limiting conditions. Water stress was induced by applying 50 % of estimated daily water use from days of year 184-208. M4 was able to deliver similar CO₂, at a significantly reduced water use, compared to SO4 grafting. In turn, this resulted in enhanced canopy water use efficiency (NCER/T_c ratio) quantified as +15.1 % during water stress and +21.7 % at re-watering. Untargeted metabolomics showed a similar modulation of brassinosteroids and ABA between the two rootstocks, whereas the up accumulation of cytokinins and gibberellins under drought was peculiar of M4 grafted vines. The increase in gibberellins, together with a concurrent down accumulation of chlorophyll precursors and catabolites and an up accumulation of folates in M4 rootstock suggests that the capacity of limiting reactive-oxygen-species and redox imbalance under drought stress was improved. Finally, distinctive osmolyte accumulation patterns could be observed, with SO4 investing more on proline and glycine-betaine content and M4 primarily showing polyols accumulation.

Whole-Genome Sequences of Two New Caballeronia Strains Isolated from Cryoturbated Peat Circles of the Permafrost-Affected Eastern European Tundra

Annotated genomes of Caballeronia strains SBC1 and SBC2 from acidic permafrost suggest a new species with a facultative lifestyle via oxygen and nitrate respiration. Thus, a contribution to nitrogen cycling in cold and low-pH environments is anticipated.

Annotated genomes of Caballeronia strains SBC1 and SBC2 from acidic permafrost suggest a new species with a facultative lifestyle via oxygen and nitrate respiration. Thus, a contribution to nitrogen cycling in cold and low-pH environments is anticipated.

Machine learning: A powerful tool for gene function prediction in plants

Recent advances in sequencing and informatic technologies have led to a deluge of publicly available genomic data. While it is now relatively easy to sequence, assemble, and identify genic regions in diploid plant genomes, functional annotation of these genes is still a challenge. Over the past decade, there has been a steady increase in studies utilizing machine learning algorithms for various aspects of functional prediction, because these algorithms are able to integrate large amounts of heterogeneous data and detect patterns inconspicuous through rule-based approaches. The goal of this review is to introduce experimental plant biologists to machine learning, by describing how it is currently being used in gene function prediction to gain novel biological insights. In this review, we discuss specific applications of machine learning in identifying structural features in sequenced genomes, predicting interactions between different cellular components, and predicting gene function and organismal phenotypes. Finally, we also propose strategies for stimulating functional discovery using machine learning-based approaches in plants.

Combining Molecular Weight Fractionation and Metabolomics to Elucidate the Bioactivity of Vegetal Protein Hydrolysates in Tomato Plants

The comprehension of the bioactive fractions involved in the biostimulant activity of plant derived protein hydrolysates (PH) is a complex task, but it can also lead to significant improvements in the production of more effective plant biostimulants. The aim of this work is to shed light onto the bioactivity of different PH dialysis fractions (PH1 < 0.5-1 kDa; PH2 > 0.5-1 kDa; PH3 < 8-10 kDa; PH4 > 8-10 kDa) of a commercial PH-based biostimulant through a combined in vivo bioassay and metabolomics approach. A first tomato rooting bioassay investigated the auxin-like activity of PH and its fractions, each of them at three nitrogen levels (3, 30, and 300 mg L^-1 of N) in comparison with a negative control (water) and a positive control (indole-3-butyric acid, IBA). Thereafter, a second experiment was carried out where metabolomics was applied to elucidate the biochemical changes imposed by the PH and its best performing fraction (both at 300 mg L^-1 of N) in comparison to water and IBA. Overall, both the PH and its fractions increased the root length of tomato cuttings, compared to negative control. Moreover, the highest root length was obtained in the treatment PH1 following foliar application. Metabolomics allowed highlighting a response to PH1 that involved changes at phytohormones and secondary metabolite level. Notably, such metabolic reprogramming supported the effect on rooting of tomato cuttings, being shared with the response induced by the positive control IBA. Taken together, the outcome of in vivo assays and metabolomics indicate an auxin-like activity of the selected PH1 fraction.

Pontiella desulfatans gen. nov., sp. nov., and Pontiella sulfatireligans sp. nov., Two Marine Anaerobes of the Pontiellaceae fam. nov. Producing Sulfated Glycosaminoglycan-like Exopolymers

Recently, we isolated two marine strains, F1^T and F21^T, which together with Kiritimatiella glycovorans L21-Fru-AB^T are the only pure cultures of the class Kiritimatiellae within the phylum Verrucomicrobiota. Here, we present an in-depth genome-guided characterization of both isolates with emphasis on their exopolysaccharide synthesis. The strains only grew fermentatively on simple carbohydrates and sulfated polysaccharides. Strains F1^T, F21^T and K. glycovorans reduced elemental sulfur, ferric citrate and anthraquinone-2,6-disulfonate during anaerobic growth on sugars. Both strains produced exopolysaccharides during stationary phase, probably with intracellularly stored glycogen as energy and carbon source. Exopolysaccharides included N-sulfated polysaccharides probably containing hexosamines and thus resembling glycosaminoglycans. This implies that the isolates can both degrade and produce sulfated polysaccharides. Both strains encoded an unprecedently high number of glycoside hydrolase genes (422 and 388, respectively), including prevalent alpha-L-fucosidase genes, which may be necessary for degrading complex sulfated polysaccharides such as fucoidan. Strain F21^T encoded three putative glycosaminoglycan sulfotransferases and a putative sulfate glycosaminoglycan biosynthesis gene cluster. Based on phylogenetic and chemotaxonomic analyses, we propose the taxa Pontiella desulfatans F1^T gen. nov., sp. nov. and Pontiella sulfatireligans F21^T sp. nov. as representatives of the Pontiellaceae fam. nov. within the class Kiritimatiellae.

MAPPS: A Web-Based Tool for Metabolic Pathway Prediction and Network Analysis in the Postgenomic Era

Comparative and evolutionary analyses of metabolic networks have a wide range of applications, ranging from research into metabolic evolution through to practical applications in drug development, synthetic biology, and biodegradation. We present MAPPS: Metabolic network Analysis and Pathway Prediction Server (https://mapps.lums.edu.pk), a web-based tool to study functions and evolution of metabolic networks using traditional and 'omics data sets. MAPPS provides diverse functionalities including an interactive interface, graphical visualization of results, pathway prediction and network comparison, identification of potential drug targets, in silico metabolic engineering, host-microbe interactions, and ancestral network building. Importantly, MAPPS also allows users to upload custom data, thus enabling metabolic analyses on draft and custom genomes, and has an 'omics pipeline to filter pathway results, making it relevant in today's postgenomic era.

Cannabinomics: Application of Metabolomics in Cannabis (Cannabis sativa L.) Research and Development

Cannabis (Cannabis sativa L.) is a complex, polymorphic plant species, which produces a vast array of bioactive metabolites, the two major chemical groups being cannabinoids and terpenoids. Nonetheless, the psychoactive cannabinoid tetrahydrocannabinol (Δ 9 -THC) and the non-psychoactive cannabidiol (CBD), are the two major cannabinoids that have monopolized the research interest. Currently, more than 600 Cannabis varieties are commercially available, providing access to a multitude of potent extracts with complex compositions, whose genetics are largely inconclusive. Recently introduced legislation on Cannabis cultivation in many countries represents a great opportunity, but at the same time, a great challenge for Cannabis research and development (R&D) toward applications in the pharmaceutical, food, cosmetics, and agrochemical industries. Based on its versatility and unique capabilities in the deconvolution of the metabolite composition of complex matrices, metabolomics represents an ideal bioanalytical tool that could greatly assist and accelerate Cannabis R&D. Among others, Cannabis metabolomics or cannabinomics can be applied in the taxonomy of Cannabis varieties in chemovars, the research on the discovery and assessment of new Cannabis-based sources of bioactivity in medicine, the development of new food products, and the optimization of its cultivation, aiming for improvements in yield and potency. Although Cannabis research is still in its infancy, it is highly foreseen that the employment of advanced metabolomics will provide insights that could assist the sector to face the aforementioned challenges. Within this context, here, the current state-of-the-art and conceptual aspects of cannabinomics are presented.

Metabolomic Responses of Maize Shoots and Roots Elicited by Combinatorial Seed Treatments With Microbial and Non-microbial Biostimulants

Microbial and non-microbial plant biostimulants have been successfully used to improve agriculture productivity in a more sustainable manner. Since the mode of action of biostimulants is still largely unknown, the present work aimed at elucidating the morpho-physiological and metabolomic changes occurring in maize (Zea mays L.) leaves and roots following seed treatment with (i) a consortium of two beneficial fungi [arbuscular mycorrhizal fungi (AMF) and Trichoderma koningii TK7] and rhizobacteria, (ii) a protein hydrolyzate-based biostimulant (PH) alone, or (iii) in combination with a consortium of T. koningii TK7 and rhizobacteria. The application of PH alone or in combination with Trichoderma elicited significant increases (+16.6%) in the shoot biomass compared to untreated maize plants, whereas inoculation with AMF + Trichoderma elicited significant increases in root dry biomass (+48.0%) compared to untreated plants. Distinctive metabolomic signatures were achieved from the different treatments, hence suggesting that different molecular processes were involved in the plants response to the biostimulants. The metabolic reprogramming triggered by the treatments including the protein hydrolyzate was hierarchically more pronounced than the application of microorganisms alone. Most of the differential metabolites could be ascribed to the secondary metabolism, with phenylpropanoids and terpenes being the most represented compounds. The application of PH triggered an accumulation of secondary metabolites, whereas the opposite trend of accumulation was seen in the case of microorganisms alone. The increase in biomass could be related to two processes, namely the modulation of the multilayer phytohormone interaction network and a possible increase in nitrogen use efficiency via the GS-GOGAT system.

Insect-Symbiont Gene Expression in the Midgut Bacteriocytes of a Blood-Sucking Parasite

Animals interact with a diverse array of both beneficial and detrimental microorganisms. In insects, these symbioses in many cases allow feeding on nutritionally unbalanced diets. It is, however, still not clear how are obligate symbioses maintained at the cellular level for up to several hundred million years. Exact mechanisms driving host-symbiont interactions are only understood for a handful of model species and data on blood-feeding hosts with intracellular bacteria are particularly scarce. Here, we analyzed interactions between an obligately blood-sucking parasite of sheep, the louse fly Melophagus ovinus, and its obligate endosymbiont, Arsenophonus melophagi. We assembled a reference transcriptome for the insect host and used dual RNA-Seq with five biological replicates to compare expression in the midgut cells specialized for housing symbiotic bacteria (bacteriocytes) to the rest of the gut (foregut-hindgut). We found strong evidence for the importance of zinc in the system likely caused by symbionts using zinc-dependent proteases when acquiring amino acids, and for different immunity mechanisms controlling the symbionts than in closely related tsetse flies. Our results show that cellular and nutritional interactions between this blood-sucking insect and its symbionts are less intimate than what was previously found in most plant-sap sucking insects. This finding is likely interconnected to several features observed in symbionts in blood-sucking arthropods, particularly their midgut intracellular localization, intracytoplasmic presence, less severe genome reduction, and relatively recent associations caused by frequent evolutionary losses and replacements.

From the Inside Out: an Epibiotic Bdellovibrio Predator with an Expanded Genomic Complement

Bdellovibrio and like organisms are abundant environmental parasitoids of prokaryotes that show diverse predation strategies. The vast majority of studied Bdellovibrio bacteria and like organisms deploy intraperiplasmic replication inside the prey cell, while few isolates with smaller genomes consume their prey from the outside in an epibiotic manner. The novel parasitoid "Candidatus Bdellovibrio qaytius" was isolated from a eutrophic freshwater pond in British Columbia, where it was a continual part of the microbial community. "Ca Bdellovibrio qaytius" was found to preferentially prey on the betaproteobacterium Paraburkholderia fungorum without entering the periplasm. Despite its epibiotic replication strategy, "Ca Bdellovibrio" encodes a large genomic complement more similar to that of complex periplasmic predators. Functional genomic annotation further revealed several biosynthesis pathways not previously found in epibiotic predators, indicating that "Ca Bdellovibrio" represents an intermediate phenotype and at the same time narrowing down the genomic complement specific to epibiotic predators. In phylogenetic analysis, "Ca Bdellovibrio qaytius" occupies a widely distributed, but poorly characterized, basal cluster within the genus Bdellovibrio This suggests that epibiotic predation might be a common predation type in nature and that epibiotic predation could be the ancestral predation type in the genus.IMPORTANCE Bdellovibrio and like organisms are bacteria that prey on other bacteria and are widespread in the environment. Most of the known Bdellovibrio species enter the space between the inner and outer prey membrane, where they consume their prey cells. However, one Bdellovibrio species has been described that consumes its prey from the outside. Here, we describe "Ca Bdellovibrio qaytius," a novel member of the genus Bdellovibrio that also remains outside the prey cell throughout its replication cycle. Unexpectedly, the genome of "Ca Bdellovibrio" is much more similar to the genomes of intracellular predators than to the species with a similar life cycle. Since "Ca Bdellovibrio" is also a basal representative of this genus, we hypothesize that extracellular predation could be the ancestral predation strategy.

The MetaCyc database of metabolic pathways and enzymes - a 2019 update

MetaCyc (MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains 2749 pathways derived from more than 60 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc are evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in BioCyc.org and other genomic portals. This article provides an update on the developments in MetaCyc during September 2017 to August 2019, up to version 23.1. Some of the topics that received intensive curation during this period include cobamides biosynthesis, sterol metabolism, fatty acid biosynthesis, lipid metabolism, carotenoid metabolism, protein glycosylation, antibiotics and cytotoxins biosynthesis, siderophore biosynthesis, bioluminescence, vitamin K metabolism, brominated compound metabolism, plant secondary metabolism and human metabolism. Other additions include modifications to the GlycanBuilder software that enable displaying glycans using symbolic representation, improved graphics and fonts for web displays, improvements in the PathoLogic component of Pathway Tools, and the optional addition of regulatory information to pathway diagrams.

Nutraceutical Profiles of Two Hydroponically Grown Sweet Basil Cultivars as Affected by the Composition of the Nutrient Solution and the Inoculation With Azospirillum brasilense

Sweet basil (Ocimum basilicum L.) is one of the most produced aromatic herbs in the world, exploiting hydroponic systems. It has been widely assessed that macronutrients, like nitrogen (N) and sulfur (S), can strongly affect the organoleptic qualities of agricultural products, thus influencing their nutraceutical value. In addition, plant-growth-promoting rhizobacteria (PGPR) have been shown to affect plant growth and quality. Azospirillum brasilense is a PGPR able to colonize the root system of different crops, promoting their growth and development and influencing the acquisition of mineral nutrients. On the bases of these observations, we aimed at investigating the impact of both mineral nutrients supply and rhizobacteria inoculation on the nutraceutical value on two different sweet basil varieties, i.e., Genovese and Red Rubin. To these objectives, basil plants have been grown in hydroponics, with nutrient solutions fortified for the concentration of either S or N, supplied as SO₄ ^2- or NO₃ ^-, respectively. In addition, plants were either non-inoculated or inoculated with A. brasilense. At harvest, basil plants were assessed for the yield and the nutraceutical properties of the edible parts. The cultivation of basil plants in the fortified nutrient solutions showed a general increasing trend in the accumulation of the fresh biomass, albeit the inoculation with A. brasilense did not further promote the growth. The metabolomic analyses disclosed a strong effect of treatments on the differential accumulation of metabolites in basil leaves, producing the modulation of more than 400 compounds belonging to the secondary metabolism, as phenylpropanoids, isoprenoids, alkaloids, several flavonoids, and terpenoids. The primary metabolism that resulted was also influenced by the treatments showing changes in the fatty acid, carbohydrates, and amino acids metabolism. The amino acid analysis revealed that the treatments induced an increase in arginine (Arg) content in the leaves, which has been shown to have beneficial effects on human health. In conclusion, between the two cultivars studied, Red Rubin displayed the most positive effect in terms of nutritional value, which was further enhanced following A. brasilense inoculation.

Microbial life under ice: Metagenome diversity and in situ activity of Verrucomicrobia in seasonally ice-covered Lakes

Northern lakes are ice-covered for a large part of the year, yet our understanding of microbial diversity and activity during winter lags behind that of the ice-free period. In this study, we investigated under-ice diversity and metabolism of Verrucomicrobia in seasonally ice-covered lakes in temperate and boreal regions of Quebec, Canada using 16S rRNA sequencing, metagenomics and metatranscriptomics. Verrucomicrobia, particularly the V1, V3 and V4 subdivisions, were abundant during ice-covered periods. A diversity of Verrucomicrobia genomes were reconstructed from Quebec lake metagenomes. Several genomes were associated with the ice-covered period and were represented in winter metatranscriptomes, supporting the notion that Verrucomicrobia are metabolically active under ice. Verrucomicrobia transcriptome analysis revealed a range of metabolisms potentially occurring under ice, including carbohydrate degradation, glycolate utilization, scavenging of chlorophyll degradation products, and urea use. Genes for aerobic sulfur and hydrogen oxidation were expressed, suggesting chemolithotrophy may be an adaptation to conditions where labile carbon may be limited. The expression of genes for flagella biosynthesis and chemotaxis was detected, suggesting Verrucomicrobia may be actively sensing and responding to winter nutrient pulses, such as phytoplankton blooms. These results increase our understanding on the diversity and metabolic processes occurring under ice in northern lakes ecosystems.© 2018 Society for Applied Microbiology and John Wiley & Sons Ltd.

Molecular docking, pharmacophore based virtual screening and molecular dynamics studies towards the identification of potential leads for the management of H. pylori

The enzyme pantothenate synthetase panC is one of the potential new antimicrobial drug targets, but it is poorly characterized in H. pylori. H. pylori infection can cause gastric cancer and the management of H. pylori infection is crucial in various gastric ulcers and gastric cancer. The current study describes the use of innovative drug discovery and design approaches like comparative metabolic pathway analysis (Metacyc), exploration of database of essential genes (DEG), homology modelling, pharmacophore based virtual screening, ADMET studies and molecular dynamics simulations in identifying potential lead compounds for the H. pylori specific panC. The top ranked virtual hits STOCK1N-60270, STOCK1N-63040, STOCK1N-44424 and STOCK1N-63231 can act as templates for synthesis of new H. pylori inhibitors and they hold a promise in the management of gastric cancers caused by H. pylori.