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Ramaboli MC, Ocvirk S, Khan Mirzaei M, Eberhart BL, Valdivia-Garcia M, Metwaly A, Neuhaus K, Barker G, Ru J, Nesengani LT, Mahdi-Joest D, Wilson AS, Joni SK, Layman DC, Zheng J, Mandal R, Chen Q, Perez MR, Fortuin S, Gaunt B, Wishart D, Methé B, Haller D, Li JV, Deng L, Swart R, O'Keefe SJD. Diet changes due to urbanization in South Africa are linked to microbiome and metabolome signatures of Westernization and colorectal cancer. Nat Commun 2024; 15:3379. [PMID: 38643180 PMCID: PMC11032404 DOI: 10.1038/s41467-024-46265-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 02/15/2024] [Indexed: 04/22/2024] Open
Abstract
Transition from traditional high-fiber to Western diets in urbanizing communities of Sub-Saharan Africa is associated with increased risk of non-communicable diseases (NCD), exemplified by colorectal cancer (CRC) risk. To investigate how urbanization gives rise to microbial patterns that may be amenable by dietary intervention, we analyzed diet intake, fecal 16 S bacteriome, virome, and metabolome in a cross-sectional study in healthy rural and urban Xhosa people (South Africa). Urban Xhosa individuals had higher intakes of energy (urban: 3,578 ± 455; rural: 2,185 ± 179 kcal/d), fat and animal protein. This was associated with lower fecal bacteriome diversity and a shift from genera favoring degradation of complex carbohydrates (e.g., Prevotella) to taxa previously shown to be associated with bile acid metabolism and CRC. Urban Xhosa individuals had higher fecal levels of deoxycholic acid, shown to be associated with higher CRC risk, but similar short-chain fatty acid concentrations compared with rural individuals. Fecal virome composition was associated with distinct gut bacterial communities across urbanization, characterized by different dominant host bacteria (urban: Bacteriodota; rural: unassigned taxa) and variable correlation with fecal metabolites and dietary nutrients. Food and skin microbiota samples showed compositional differences along the urbanization gradient. Rural-urban dietary transition in South Africa is linked to major changes in the gut microbiome and metabolome. Further studies are needed to prove cause and identify whether restoration of specific components of the traditional diet will arrest the accelerating rise in NCDs in Sub-Saharan Africa.
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Affiliation(s)
- M C Ramaboli
- African Microbiome Institute, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - S Ocvirk
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Intestinal Microbiology Research Group, German Institute of Human Nutrition, Potsdam, Germany
- ZIEL - Institute for Food and Health, Technical University of Munich, Freising, Germany
| | - M Khan Mirzaei
- Institute of Virology, Helmholtz Centre Munich - German Research Centre for Environmental Health, Neuherberg, Germany
- Chair of Microbial Disease Prevention, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - B L Eberhart
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - M Valdivia-Garcia
- Section of Nutrition, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - A Metwaly
- Chair of Nutrition and Immunology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - K Neuhaus
- Core Facility Microbiome, ZIEL - Institute for Food and Health, Technical University of Munich, Freising, Germany
| | - G Barker
- Section of Nutrition, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - J Ru
- Institute of Virology, Helmholtz Centre Munich - German Research Centre for Environmental Health, Neuherberg, Germany
- Chair of Microbial Disease Prevention, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - L T Nesengani
- Department of Agriculture and Animal Health, University of South Africa, Pretoria, South Africa
| | - D Mahdi-Joest
- Intestinal Microbiology Research Group, German Institute of Human Nutrition, Potsdam, Germany
| | - A S Wilson
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - S K Joni
- Department of Nutrition and Dietetics, School of Public Health, University of the Western Cape, Cape Town, South Africa
| | - D C Layman
- Department of Nutrition and Dietetics, School of Public Health, University of the Western Cape, Cape Town, South Africa
| | - J Zheng
- The Metabolomics Innovation Centre & Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - R Mandal
- The Metabolomics Innovation Centre & Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Q Chen
- Section of Nutrition, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - M R Perez
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - S Fortuin
- African Microbiome Institute, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - B Gaunt
- Zithulele Hospital, Mqanduli District, Mqanduli, Eastern Cape Province, South Africa
| | - D Wishart
- The Metabolomics Innovation Centre & Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - B Methé
- Center for Medicine and the Microbiome, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - D Haller
- ZIEL - Institute for Food and Health, Technical University of Munich, Freising, Germany
- Chair of Nutrition and Immunology, TUM School of Life Sciences, Technical University of Munich, Freising, Germany
| | - J V Li
- Section of Nutrition, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - L Deng
- Institute of Virology, Helmholtz Centre Munich - German Research Centre for Environmental Health, Neuherberg, Germany
- Chair of Microbial Disease Prevention, School of Life Sciences, Technical University of Munich, Freising, Germany
| | - R Swart
- Department of Nutrition and Dietetics, School of Public Health, University of the Western Cape, Cape Town, South Africa
| | - S J D O'Keefe
- African Microbiome Institute, Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
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Potgieter MG, Nel AJM, Fortuin S, Garnett S, Wendoh JM, Tabb DL, Mulder NJ, Blackburn JM. MetaNovo: An open-source pipeline for probabilistic peptide discovery in complex metaproteomic datasets. PLoS Comput Biol 2023; 19:e1011163. [PMID: 37327214 DOI: 10.1371/journal.pcbi.1011163] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 05/08/2023] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Microbiome research is providing important new insights into the metabolic interactions of complex microbial ecosystems involved in fields as diverse as the pathogenesis of human diseases, agriculture and climate change. Poor correlations typically observed between RNA and protein expression datasets make it hard to accurately infer microbial protein synthesis from metagenomic data. Additionally, mass spectrometry-based metaproteomic analyses typically rely on focused search sequence databases based on prior knowledge for protein identification that may not represent all the proteins present in a set of samples. Metagenomic 16S rRNA sequencing only targets the bacterial component, while whole genome sequencing is at best an indirect measure of expressed proteomes. Here we describe a novel approach, MetaNovo, that combines existing open-source software tools to perform scalable de novo sequence tag matching with a novel algorithm for probabilistic optimization of the entire UniProt knowledgebase to create tailored sequence databases for target-decoy searches directly at the proteome level, enabling metaproteomic analyses without prior expectation of sample composition or metagenomic data generation and compatible with standard downstream analysis pipelines. RESULTS We compared MetaNovo to published results from the MetaPro-IQ pipeline on 8 human mucosal-luminal interface samples, with comparable numbers of peptide and protein identifications, many shared peptide sequences and a similar bacterial taxonomic distribution compared to that found using a matched metagenome sequence database-but simultaneously identified many more non-bacterial peptides than the previous approaches. MetaNovo was also benchmarked on samples of known microbial composition against matched metagenomic and whole genomic sequence database workflows, yielding many more MS/MS identifications for the expected taxa, with improved taxonomic representation, while also highlighting previously described genome sequencing quality concerns for one of the organisms, and identifying an experimental sample contaminant without prior expectation. CONCLUSIONS By estimating taxonomic and peptide level information directly on microbiome samples from tandem mass spectrometry data, MetaNovo enables the simultaneous identification of peptides from all domains of life in metaproteome samples, bypassing the need for curated sequence databases to search. We show that the MetaNovo approach to mass spectrometry metaproteomics is more accurate than current gold standard approaches of tailored or matched genomic sequence database searches, can identify sample contaminants without prior expectation and yields insights into previously unidentified metaproteomic signals, building on the potential for complex mass spectrometry metaproteomic data to speak for itself.
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Affiliation(s)
- Matthys G Potgieter
- Computational Biology Division, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
- Division of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Andrew J M Nel
- Division of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Suereta Fortuin
- Division of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Shaun Garnett
- Division of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Jerome M Wendoh
- Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - David L Tabb
- Division of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences; African Microbiome Institute; South African Tuberculosis Bioinformatics Initiative; Stellenbosch University, Cape Town, South Africa
| | - Nicola J Mulder
- Computational Biology Division, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
- Institute of Infectious Disease & Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Jonathan M Blackburn
- Division of Chemical and Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
- Institute of Infectious Disease & Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
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Cuttler K, Fortuin S, Müller-Nedebock AC, Vlok M, Cloete R, Bardien S. Proteomics analysis of the p.G849D variant in neurexin 2 alpha may reveal insight into Parkinson’s disease pathobiology. Front Aging Neurosci 2022; 14:1002777. [DOI: 10.3389/fnagi.2022.1002777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 11/08/2022] [Indexed: 12/02/2022] Open
Abstract
Parkinson’s disease (PD), the fastest-growing neurological disorder globally, has a complex etiology. A previous study by our group identified the p.G849D variant in neurexin 2 (NRXN2), encoding the synaptic protein, NRXN2α, as a possible causal variant of PD. Therefore, we aimed to perform functional studies using proteomics in an attempt to understand the biological pathways affected by the variant. We hypothesized that this may reveal insight into the pathobiology of PD. Wild-type and mutant NRXN2α plasmids were transfected into SH-SY5Y cells. Thereafter, total protein was extracted and prepared for mass spectrometry using a Thermo Scientific Fusion mass spectrometer equipped with a Nanospray Flex ionization source. The data were then interrogated against the UniProt H. sapiens database and afterward, pathway and enrichment analyses were performed using in silico tools. Overexpression of the wild-type protein led to the enrichment of proteins involved in neurodegenerative diseases, while overexpression of the mutant protein led to the decline of proteins involved in ribosomal functioning. Thus, we concluded that the wild-type NRXN2α may be involved in pathways related to the development of neurodegenerative disorders, and that biological processes related to the ribosome, transcription, and tRNA, specifically at the synapse, could be an important mechanism in PD. Future studies targeting translation at the synapse in PD could therefore provide further information on the pathobiology of the disease.
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Fortuin S, Soares NC. The Integration of Proteomics and Metabolomics Data Paving the Way for a Better Understanding of the Mechanisms Underlying Microbial Acquired Drug Resistance. Front Med (Lausanne) 2022; 9:849838. [PMID: 35602483 PMCID: PMC9120609 DOI: 10.3389/fmed.2022.849838] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 04/14/2022] [Indexed: 11/13/2022] Open
Abstract
Due to an increase in the overuse of antimicrobials and accelerated incidence of drug resistant pathogens, antimicrobial resistance has become a global health threat. In particular, bacterial antimicrobial resistance, in both hospital and community acquired transmission, have been found to be the leading cause of death due to infectious diseases. Understanding the mechanisms of bacterial drug resistance is of clinical significance irrespective of hospital or community acquired since it plays an important role in the treatment strategy and controlling infectious diseases. Here we highlight the advances in mass spectrometry-based proteomics impact in bacterial proteomics and metabolomics analysis- focus on bacterial drug resistance. Advances in omics technologies over the last few decades now allows multi-omics studies in order to obtain a comprehensive understanding of the biochemical alterations of pathogenic bacteria in the context of antibiotic exposure, identify novel biomarkers to develop new drug targets, develop time-effectively screen for drug susceptibility or resistance using proteomics and metabolomics.
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Affiliation(s)
- Suereta Fortuin
- African Microbiome Institute, General Internal Medicine, Stellenbosch University, Cape Town, South Africa
- *Correspondence: Suereta Fortuin
| | - Nelson C. Soares
- College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
- Nelson C. Soares
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Fortuin S, Iradukunda J, Nel AJ, Blackburn JM, Soares NC. Liquid chromatography mass spectrometry-based proteomics of Escherichia coli single colony. MethodsX 2021; 8:101277. [PMID: 34434797 PMCID: PMC8374269 DOI: 10.1016/j.mex.2021.101277] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 02/14/2021] [Indexed: 01/17/2023] Open
Abstract
The Escherichia coli proteome is the most extensively characterized and studied of all prokaryotic proteomes. Despite this, large scale bacterial proteomics experiments performed on E. coli cells grown in liquid cultures have failed to identify key virulence factors thought to be important determinants in establishing bacterial infections. It seems likely that many important determinants associated with virulence and host cell adhesion are exclusively expressed during growth in biofilms, which can be crudely mimicked on solid media. This method describes a simple workflow to characterize the unique proteome signature of individual, isolated single colonies, using E. coli K12 strain grown on solid media as a model system. The workflow thus provides a means to explore the proteomes of minimally passaged clinical isolates of bacteria grown on primary culture plates and to identify both unique and differentially expressed proteins contained therein. Value of the method: - Simple mass spectrometry-based proteomics workflow to characterise the proteome of single colony forming units - Enables exploration of the proteomes of minimally passaged clinical isolates from primary culture plates - Identification of virulence factors expressed in true or mimicked biofilms that may be missed in liquid cultures Method name: E. coli single colony proteome analysis
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Affiliation(s)
- Suereta Fortuin
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town, Anzio, Observatory, Cape Town 7925, South Africa
| | - John Iradukunda
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town, Anzio, Observatory, Cape Town 7925, South Africa
| | - Andrew Jm Nel
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town, Anzio, Observatory, Cape Town 7925, South Africa
| | - Jonathan M Blackburn
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town, Anzio, Observatory, Cape Town 7925, South Africa.,Institute of Infectious Disease & Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Anzio, Observatory, Cape Town 7925, South Africa
| | - Nelson C Soares
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates.,College of Pharmacy, Department of Medicinal Chemistry, University of Sharjah, Sharjah, United Arab Emirates
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Fortuin S, Nel AJM, Blackburn JM, Soares NC. Comparison between the proteome of Escherichia coli single colony and during liquid culture. J Proteomics 2020; 228:103929. [PMID: 32800795 DOI: 10.1016/j.jprot.2020.103929] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 07/29/2020] [Accepted: 08/04/2020] [Indexed: 02/06/2023]
Abstract
Most bacterial proteomic studies done to date utilise bacterial cells harvested from liquid culture media. However, it is widely accepted that many important determinants associated with virulence and host cell adhesion are exclusively expressed during growth on solid media, as a crude mimic of true biofilms. Here, we compare the observed proteome of Escherichia coli K12 from isolated single colonies on solid media with those observed at different growth phases in liquid culture; i.e. early-log, mid-log, early-, mid- and late-stationary growth phases. A total of 2044 protein groups covering approximately 47% of the total proteome were identified across all studied conditions, including 1650 proteins identified from single colonies and 1679 proteins from liquid cultured cells. Label-free quantitative analysis revealed that the E. coli proteome of single colonies on a solid agar differs from that observed in liquid culture. Notably, the presence of proteins in the Suf-operon that are involved in iron mobilisation and swarming motility was associated exclusively with single colony profiles, whereas proteins involved in motility such as motA, motB, fliH, flip, fliD and fliJ were associated exclusively with cells grown in liquid culture. The data presented here provide a valuable resource for understanding the role of key proteins within microenvironments surrounding E. coli single colonies. SIGNIFICANCE: To date, most proteomics studies have used E. coli cells harvested from liquid culture media even though many important determinants associated with virulence and host cell adhesion are exclusively expressed during growth on solid media. In this study, we compare the observed proteome of E. coli K12 from isolated single colonies on solid media with those observed at different growth phases in liquid culture; i.e. early-log, mid-log, early-, mid- and late-stationary growth phases. By using label-free quantitative analysis we demonstrate that the E. coli proteome of single colonies on a solid agar differs from that observed in liquid culture with an overlap of 68% of proteins between the two culture conditions. Our analysis further reveal the presence of proteins in the Suf-operon that are involved in iron mobilisation and swarming motility was associated exclusively with single colony profiles. While those proteins involved in motility such as motA, motB, fliH, flip, fliD and fliJ were associated exclusively with cells grown in liquid culture. By comparison to E. coli proteomic data available on liquid culture and solid media, this research represents a first effort to describe the differential expression of key E. coli proteins within microenvironments surrounding single colonies.
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Affiliation(s)
- Suereta Fortuin
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town. Cape Town, South Africa
| | - Andrew J M Nel
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town. Cape Town, South Africa
| | - Jonathan M Blackburn
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, Faculty of Health Sciences, University of Cape Town. Cape Town, South Africa; Institute of Infectious Disease & Molecular Medicine, Faculty of Health Sciences, University of Cape Town. Cape Town, South Africa.
| | - Nelson C Soares
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates; College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates.
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Machado KCT, Fortuin S, Tomazella GG, Fonseca AF, Warren RM, Wiker HG, de Souza SJ, de Souza GA. On the Impact of the Pangenome and Annotation Discrepancies While Building Protein Sequence Databases for Bacteria Proteogenomics. Front Microbiol 2019; 10:1410. [PMID: 31281302 PMCID: PMC6596428 DOI: 10.3389/fmicb.2019.01410] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 06/05/2019] [Indexed: 01/19/2023] Open
Abstract
In proteomics, peptide information within mass spectrometry (MS) data from a specific organism sample is routinely matched against a protein sequence database that best represent such organism. However, if the species/strain in the sample is unknown or genetically poorly characterized, it becomes challenging to determine a database which can represent such sample. Building customized protein sequence databases merging multiple strains for a given species has become a strategy to overcome such restrictions. However, as more genetic information is publicly available and interesting genetic features such as the existence of pan- and core genes within a species are revealed, we questioned how efficient such merging strategies are to report relevant information. To test this assumption, we constructed databases containing conserved and unique sequences for 10 different species. Features that are relevant for probabilistic-based protein identification by proteomics were then monitored. As expected, increase in database complexity correlates with pangenomic complexity. However, Mycobacterium tuberculosis and Bordetella pertussis generated very complex databases even having low pangenomic complexity. We further tested database performance by using MS data from eight clinical strains from M. tuberculosis, and from two published datasets from Staphylococcus aureus. We show that by using an approach where database size is controlled by removing repeated identical tryptic sequences across strains/species, computational time can be reduced drastically as database complexity increases.
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Affiliation(s)
- Karla C T Machado
- Bioinformatics Multidisciplinary Environment, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Suereta Fortuin
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research/SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Gisele Guicardi Tomazella
- Bioinformatics Multidisciplinary Environment, Universidade Federal do Rio Grande do Norte, Natal, Brazil
- The Gade Research Group for Infection and Immunity, Department of Clinical Science, University of Bergen, Bergen, Norway
- The Institute of Bioinformatics and Biotechnology, Natal, Brazil
| | - Andre F Fonseca
- Bioinformatics Multidisciplinary Environment, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Robin Mark Warren
- DST/NRF Centre of Excellence for Biomedical Tuberculosis Research/SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch, South Africa
| | - Harald G Wiker
- The Gade Research Group for Infection and Immunity, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Sandro Jose de Souza
- Bioinformatics Multidisciplinary Environment, Universidade Federal do Rio Grande do Norte, Natal, Brazil
- The Brain Institute, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | - Gustavo Antonio de Souza
- Bioinformatics Multidisciplinary Environment, Universidade Federal do Rio Grande do Norte, Natal, Brazil
- Department of Biochemistry, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
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Kalule JB, Fortuin S, Calder B, Robberts L, Keddy KH, Nel AJM, Garnett S, Nicol M, Warner DF, Soares NC, Blackburn JM. Proteomic comparison of three clinical diarrhoeagenic drug-resistant Escherichia coli isolates grown on CHROMagar™STEC media. J Proteomics 2017; 180:25-35. [PMID: 28887208 DOI: 10.1016/j.jprot.2017.09.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Revised: 08/21/2017] [Accepted: 09/02/2017] [Indexed: 02/06/2023]
Abstract
Shiga-toxin-producing Escherichia coli (STEC) and enteropathogenic Escherichia coli (EPEC) are key diarrhoea-causing foodborne pathogens. We used proteomics to characterize the virulence and antimicrobial resistance protein profiles of three clinical pathogenic E. coli isolates (two EPEC [one resistant to ciprofloxacin] and one STEC) cultured on CHROMagar™STEC solid media after minimal laboratory passage. We identified 4767 unique peptides from 1630 protein group across all three clinical E. coli strains. Label-free proteomic analysis allowed the identification of virulence and drug resistance proteins that were unique to each of the clinical isolates compared in this study. The B subunit of Shiga toxin, ToxB, was uniquely detected in the STEC strain while several other virulence factors including SheA, OmpF, OmpC and OmpX were significantly more abundant in the STEC strain. The ciprofloxacin resistant EPEC isolate possessed reduced levels of key virulence proteins compared to the ciprofloxacin susceptible EPEC and STEC strains. Parallel reaction monitoring assays validated the presence of biologically relevant proteins across biologically-replicated cultures. Propagation of clinical isolates on a relevant solid medium followed by mass spectrometry analysis represents a convenient means to quantify virulence factors and drug resistance determinants that might otherwise be lost through extensive in vitro passage in enteropathogenic bacteria. SIGNIFICANCE Through the use of quantitative proteomics, we have characterized the virulence and antimicrobial resistance attributes of three clinically isolated, pathogenic E. coli strains cultured on solid media. Our results provide new, quantitative data on the expressed proteomes of these tellurite-resistant, diarrhoeagenic E. coli strains and reveal a subset of antimicrobial resistance and virulence proteins that are differentially abundant between these clinical strains. Our quantitative proteomics-based approach should thus have applicability in microbiological diagnostic labs for the identification of pathogenic/drug resistant E. coli in the future.
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Affiliation(s)
- John Bosco Kalule
- Division of Medical Microbiology, Department of Pathology, University of Cape Town, South Africa
| | - Suereta Fortuin
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Bridget Calder
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Lourens Robberts
- Division of Medical Microbiology, Department of Pathology, University of Cape Town, South Africa
| | - Karen H Keddy
- Bacteriology Division, Centre for Enteric Diseases, National Institute for Communicable Diseases, Sandringham, Johannesburg, South Africa; Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Andrew J M Nel
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Shaun Garnett
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Mark Nicol
- Division of Medical Microbiology, Department of Pathology, University of Cape Town, South Africa; Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town, South Africa
| | - Digby F Warner
- Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town, South Africa; MRC/NHLS/UCT Molecular Mycobacteriology Research Unit, DST/NRF Centre of Excellence for Biomedical TB Research, Division of Medical Microbiology, Department of Pathology, University of Cape Town, South Africa
| | - Nelson C Soares
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa.
| | - Jonathan M Blackburn
- Division of Chemical & Systems Biology, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa; Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town, South Africa.
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Fortuin S, Tomazella GG, Nagaraj N, Sampson SL, Gey van Pittius NC, Soares NC, Wiker HG, de Souza GA, Warren RM. Phosphoproteomics analysis of a clinical Mycobacterium tuberculosis Beijing isolate: expanding the mycobacterial phosphoproteome catalog. Front Microbiol 2015; 6:6. [PMID: 25713560 PMCID: PMC4322841 DOI: 10.3389/fmicb.2015.00006] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Accepted: 01/04/2015] [Indexed: 11/29/2022] Open
Abstract
Reversible protein phosphorylation, regulated by protein kinases and phosphatases, mediates a switch between protein activity and cellular pathways that contribute to a large number of cellular processes. The Mycobacterium tuberculosis genome encodes 11 Serine/Threonine kinases (STPKs) which show close homology to eukaryotic kinases. This study aimed to elucidate the phosphoproteomic landscape of a clinical isolate of M. tuberculosis. We performed a high throughput mass spectrometric analysis of proteins extracted from an early-logarithmic phase culture. Whole cell lysate proteins were processed using the filter-aided sample preparation method, followed by phosphopeptide enrichment of tryptic peptides by strong cation exchange (SCX) and Titanium dioxide (TiO2) chromatography. The MaxQuant quantitative proteomics software package was used for protein identification. Our analysis identified 414 serine/threonine/tyrosine phosphorylated sites, with a distribution of S/T/Y sites; 38% on serine, 59% on threonine and 3% on tyrosine; present on 303 unique peptides mapping to 214 M. tuberculosis proteins. Only 45 of the S/T/Y phosphorylated proteins identified in our study had been previously described in the laboratory strain H37Rv, confirming previous reports. The remaining 169 phosphorylated proteins were newly identified in this clinical M. tuberculosis Beijing strain. We identified 5 novel tyrosine phosphorylated proteins. These findings not only expand upon our current understanding of the protein phosphorylation network in clinical M. tuberculosis but the data set also further extends and complements previous knowledge regarding phosphorylated peptides and phosphorylation sites in M. tuberculosis.
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Affiliation(s)
- Suereta Fortuin
- Division of Molecular Biology and Human Genetics, Faculty Medicine and Health Sciences, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Stellenbosch University Cape Town, South Africa
| | - Gisele G Tomazella
- The Gade Research Group for Infection and Immunity, Department of Clinical Science, University of Bergen Bergen, Norway
| | | | - Samantha L Sampson
- Division of Molecular Biology and Human Genetics, Faculty Medicine and Health Sciences, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Stellenbosch University Cape Town, South Africa
| | - Nicolaas C Gey van Pittius
- Division of Molecular Biology and Human Genetics, Faculty Medicine and Health Sciences, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Stellenbosch University Cape Town, South Africa
| | - Nelson C Soares
- Faculty of Health Sciences, Institute of Infectious Disease and Molecular Medicine, University of Cape Town Cape Town, South Africa
| | - Harald G Wiker
- The Gade Research Group for Infection and Immunity, Department of Clinical Science, University of Bergen Bergen, Norway
| | - Gustavo A de Souza
- Norway Proteomics Core Facility, Department of Immunology, Oslo University Oslo, Norway
| | - Robin M Warren
- Division of Molecular Biology and Human Genetics, Faculty Medicine and Health Sciences, DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Stellenbosch University Cape Town, South Africa
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10
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Wiedner SD, Ansong C, Webb-Robertson BJ, Pederson LM, Fortuin S, Hofstad BA, Shukla AK, Panisko EA, Smith RD, Wright AT. Disparate proteome responses of pathogenic and nonpathogenic aspergilli to human serum measured by activity-based protein profiling (ABPP). Mol Cell Proteomics 2013; 12:1791-805. [PMID: 23599423 DOI: 10.1074/mcp.m112.026534] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Aspergillus fumigatus is the primary pathogen causing the devastating pulmonary disease Invasive Aspergillosis in immunocompromised individuals. There is high genomic synteny between A. fumigatus and closely related rarely pathogenic Neosartorya fischeri and Aspergillus clavatus genomes. We applied activity-based protein profiling to compare unique or overexpressed activity-based probe-reactive proteins of all three fungi over time in minimal media growth and in response to human serum. We found 360 probe-reactive proteins exclusive to A. fumigatus, including known virulence associated proteins, and 13 proteins associated with stress response exclusive to A. fumigatus culture in serum. Though the fungi are highly orthologous, A. fumigatus has a significantly greater number of ABP-reactive proteins across varied biological process. Only 50% of expected orthologs of measured A. fumigatus reactive proteins were observed in N. fischeri and A. clavatus. Activity-based protein profiling identified a number of processes that were induced by human serum in A. fumigatus relative to N. fischeri and A. clavatus. These included actin organization and assembly, transport, and fatty acid, cell membrane, and cell wall synthesis. Additionally, signaling proteins regulating vegetative growth, conidiation, and cell wall integrity, required for appropriate cellular response to external stimuli, had higher activity-based probe-protein reaction over time in A. fumigatus and N. fisheri, but not in A. clavatus. Together, we show that measured proteins and physiological processes identified solely or significantly over-represented in A. fumigatus reveal a unique adaptive response to human protein not found in closely related, but rarely pathogenic aspergilli. These unique activity-based probe-protein responses to culture condition may reveal how A. fumigatus initiates pulmonary invasion leading to Invasive Aspergillosis.
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Affiliation(s)
- Susan D Wiedner
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
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11
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Wiedner SD, Burnum KE, Pederson LM, Anderson LN, Fortuin S, Chauvigné-Hines LM, Shukla AK, Ansong C, Panisko EA, Smith RD, Wright AT. Multiplexed activity-based protein profiling of the human pathogen Aspergillus fumigatus reveals large functional changes upon exposure to human serum. J Biol Chem 2012; 287:33447-59. [PMID: 22865858 PMCID: PMC3460446 DOI: 10.1074/jbc.m112.394106] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2012] [Revised: 07/27/2012] [Indexed: 11/06/2022] Open
Abstract
Environmental adaptability is critical for survival of the fungal human pathogen Aspergillus fumigatus in the immunocompromised host lung. We hypothesized that exposure of the fungal pathogen to human serum would lead to significant alterations to the organism's physiology, including metabolic activity and stress response. Shifts in functional pathway and corresponding enzyme reactivity of A. fumigatus upon exposure to the human host may represent much needed prognostic indicators of fungal infection. To address this, we employed a multiplexed activity-based protein profiling (ABPP) approach coupled to quantitative mass spectrometry-based proteomics to measure broad enzyme reactivity of the fungus cultured with and without human serum. ABPP showed a shift from aerobic respiration to ethanol fermentation and utilization over time in the presence of human serum, which was not observed in serum-free culture. Our approach provides direct insight into this pathogen's ability to survive, adapt, and proliferate. Additionally, our multiplexed ABPP approach captured a broad swath of enzyme reactivity and functional pathways and provides a method for rapid assessment of the A. fumigatus response to external stimuli.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Ellen A. Panisko
- the Chemical and Biological Processes Development Group, Pacific Northwest National Laboratory, Richland, Washington 99352
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12
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de Souza GA, Arntzen MØ, Fortuin S, Schürch AC, Målen H, McEvoy CRE, van Soolingen D, Thiede B, Warren RM, Wiker HG. Proteogenomic analysis of polymorphisms and gene annotation divergences in prokaryotes using a clustered mass spectrometry-friendly database. Mol Cell Proteomics 2010; 10:M110.002527. [PMID: 21030493 PMCID: PMC3013451 DOI: 10.1074/mcp.m110.002527] [Citation(s) in RCA: 50] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Precise annotation of genes or open reading frames is still a difficult task that results in divergence even for data generated from the same genomic sequence. This has an impact in further proteomic studies, and also compromises the characterization of clinical isolates with many specific genetic variations that may not be represented in the selected database. We recently developed software called multistrain mass spectrometry prokaryotic database builder (MSMSpdbb) that can merge protein databases from several sources and be applied on any prokaryotic organism, in a proteomic-friendly approach. We generated a database for the Mycobacterium tuberculosis complex (using three strains of Mycobacterium bovis and five of M. tuberculosis), and analyzed data collected from two laboratory strains and two clinical isolates of M. tuberculosis. We identified 2561 proteins, of which 24 were present in M. tuberculosis H37Rv samples, but not annotated in the M. tuberculosis H37Rv genome. We were also able to identify 280 nonsynonymous single amino acid polymorphisms and confirm 367 translational start sites. As a proof of concept we applied the database to whole-genome DNA sequencing data of one of the clinical isolates, which allowed the validation of 116 predicted single amino acid polymorphisms and the annotation of 131 N-terminal start sites. Moreover we identified regions not present in the original M. tuberculosis H37Rv sequence, indicating strain divergence or errors in the reference sequence. In conclusion, we demonstrated the potential of using a merged database to better characterize laboratory or clinical bacterial strains.
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Affiliation(s)
- Gustavo A de Souza
- The Gade Institute, Section for Microbiology and Immunology, University of Bergen, N-5021 Bergen, Norway
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13
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de Souza GA, Fortuin S, Aguilar D, Pando RH, McEvoy CRE, van Helden PD, Koehler CJ, Thiede B, Warren RM, Wiker HG. Using a label-free proteomics method to identify differentially abundant proteins in closely related hypo- and hypervirulent clinical Mycobacterium tuberculosis Beijing isolates. Mol Cell Proteomics 2010; 9:2414-23. [PMID: 20190197 PMCID: PMC2984234 DOI: 10.1074/mcp.m900422-mcp200] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Although the genome of the Mycobacterium tuberculosis H37Rv laboratory strain has been available for over 10 years, it is only recently that genomic information from clinical isolates has been used to generate the hypothesis of virulence differences between different strains. In addition, the relationship between strains displaying differing virulence in an epidemiological setting and their behavior in animal models has received little attention. The potential causes for variation in virulence between strains, as determined by differential protein expression, have similarly been a neglected area of investigation. In this study, we used a label-free quantitative proteomics approach to estimate differences in protein abundance between two closely related Beijing genotypes that have been shown to be hyper- and hypovirulent on the basis of both epidemiological and mouse model studies. We were able to identify a total of 1668 proteins from both samples, and protein abundance calculations revealed that 48 proteins were over-represented in the hypovirulent isolate, whereas 53 were over-represented in the hypervirulent. Functional classification of these results shows that molecules of cell wall organization and DNA transcription regulatory proteins may have a critical influence in defining the level of virulence. The reduction in the presence of ESAT-6, other Esx-like proteins, and FbpD (MPT51) in the hypervirulent strain indicates that changes in the repertoire of highly immunogenic proteins can be a defensive process undertaken by the virulent cell. In addition, most of the previously well characterized gene targets related to virulence were found to be similarly expressed in our model. Our data support the use of proteomics as a complementary tool for genomic comparisons to understand the biology of M. tuberculosis virulence.
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Affiliation(s)
- Gustavo A de Souza
- Section for Microbiology and Immunology, The Gade Institute, University of Bergen, Bergen, Norway
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Wilde GJ, Fortuin S. Self-report and error choice: an application of the error-choice principle to the construction of personality test items. Br J Psychol 1969; 60:101-8. [PMID: 5779022 DOI: 10.1111/j.2044-8295.1969.tb01182.x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
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