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Matthew J. Gebert

Bio: Matthew J. Gebert is an academic researcher from University of Colorado Boulder. The author has contributed to research in topics: Nontuberculous mycobacteria & Microbiome. The author has an hindex of 7, co-authored 19 publications receiving 923 citations. Previous affiliations of Matthew J. Gebert include Cooperative Institute for Research in Environmental Sciences.

Papers
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Journal ArticleDOI
08 Jan 2016-Science
TL;DR: A suite of bacterial and fungal groups that contribute to nitrogen cycling and a reproducible network of decomposers that emerge on predictable time scales are found.
Abstract: Vertebrate corpse decomposition provides an important stage in nutrient cycling in most terrestrial habitats, yet microbially mediated processes are poorly understood. Here we combine deep microbial community characterization, community-level metabolic reconstruction, and soil biogeochemical assessment to understand the principles governing microbial community assembly during decomposition of mouse and human corpses on different soil substrates. We find a suite of bacterial and fungal groups that contribute to nitrogen cycling and a reproducible network of decomposers that emerge on predictable time scales. Our results show that this decomposer community is derived primarily from bulk soil, but key decomposers are ubiquitous in low abundance. Soil type was not a dominant factor driving community development, and the process of decomposition is sufficiently reproducible to offer new opportunities for forensic investigations.

359 citations

Journal ArticleDOI
TL;DR: Evaluating innate and adaptive immune responses to lysates from bacteria that differ with HIV explores the functional drivers of these compositional differences and identifies Prevotella-rich community composition most similar to healthy individuals in agrarian cultures of Malawi and Venezuela.

341 citations

Journal ArticleDOI
15 Oct 2013-eLife
TL;DR: It is shown that postmortem microbial community changes are dramatic, measurable, and repeatable in a mouse model system, allowing PMI to be estimated within approximately 3 days over 48 days, and suggested that microbial community data can be developed into a forensic tool for estimating PMI.
Abstract: Our bodies—especially our skin, our saliva, the lining of our mouth and our gastrointestinal tract—are home to a diverse collection of bacteria and other microorganisms called the microbiome. While the roles played by many of these microorganisms have yet to be identified, it is known that they contribute to the health and wellbeing of their host by metabolizing indigestible compounds, producing essential vitamins, and preventing the growth of harmful bacteria. They are important for nutrient and carbon cycling in the environment. The advent of advanced sequencing techniques has made it feasible to study the composition of this microbial community, and to monitor how it changes over time or how it responds to events such as antibiotic treatment. Sequencing studies have been used to highlight the significant differences between microbial communities found in different parts of the body, and to follow the evolution of the gut microbiome from birth. Most of these studies have focused on live animals, so little is known about what happens to the microbiome after its host dies. In particular, it is not known if the changes that occur after death are similar for all individuals. Moreover, the decomposing animal supplies nutrients and carbon to the surrounding ecosystem, but its influence on the microbial community of its immediate environment is not well understood. Now Metcalf et al. have used high-throughput sequencing to study the bacteria and other microorganisms (such as nematodes and fungi) in dead and decomposing mice, and also in the soil beneath them, over the course of 48 days. The changes were significant and also consistent across the corpses, with the microbial communities in the corpses influencing those in the soil, and vice versa. Metcalf et al. also showed that these measurements could be used to estimate the postmortem interval (the time since death) to within approximately 3 days, which suggests that the work could have applications in forensic science.

273 citations

Journal ArticleDOI
07 Nov 2018-Mbio
TL;DR: The genus Mycobacterium was consistently the most abundant genus of bacteria detected in residential showerheads, and yet mycobacterial diversity and abundances were highly variable, knowledge that advances the understanding of NTM transmission dynamics and the development of strategies to reduce exposures to these emerging pathogens is advanced.
Abstract: Bacteria within the genus Mycobacterium can be abundant in showerheads, and the inhalation of aerosolized mycobacteria while showering has been implicated as a mode of transmission in nontuberculous mycobacterial (NTM) lung infections. Despite their importance, the diversity, distributions, and environmental predictors of showerhead-associated mycobacteria remain largely unresolved. To address these knowledge gaps, we worked with citizen scientists to collect showerhead biofilm samples and associated water chemistry data from 656 households located across the United States and Europe. Our cultivation-independent analyses revealed that the genus Mycobacterium was consistently the most abundant genus of bacteria detected in residential showerheads, and yet mycobacterial diversity and abundances were highly variable. Mycobacteria were far more abundant, on average, in showerheads receiving municipal water than in those receiving well water and in U.S. households than in European households, patterns that are likely driven by differences in the use of chlorine disinfectants. Moreover, we found that water source, water chemistry, and household location also influenced the prevalence of specific mycobacterial lineages detected in showerheads. We identified geographic regions within the United States where showerheads have particularly high abundances of potentially pathogenic lineages of mycobacteria, and these "hot spots" generally overlapped those regions where NTM lung disease is most prevalent. Together, these results emphasize the public health relevance of mycobacteria in showerhead biofilms. They further demonstrate that mycobacterial distributions in showerhead biofilms are often predictable from household location and water chemistry, knowledge that advances our understanding of NTM transmission dynamics and the development of strategies to reduce exposures to these emerging pathogens.IMPORTANCE Bacteria thrive in showerheads and throughout household water distribution systems. While most of these bacteria are innocuous, some are potential pathogens, including members of the genus Mycobacterium that can cause nontuberculous mycobacterial (NTM) lung infection, an increasing threat to public health. We found that showerheads in households across the United States and Europe often harbor abundant mycobacterial communities that vary in composition depending on geographic location, water chemistry, and water source, with households receiving water treated with chlorine disinfectants having particularly high abundances of certain mycobacteria. The regions in the United States where NTM lung infections are most common were the same regions where pathogenic mycobacteria were most prevalent in showerheads, highlighting the important role of showerheads in the transmission of NTM infections.

73 citations

Journal ArticleDOI
TL;DR: The diversity, distributions, and environmental preferences of soil-dwelling mycobacteria in 143 soil samples collected from a broad range of ecosystem types are analyzed and suggest that soil is an unlikely source of manyMycobacterial infections.
Abstract: Mycobacteria are a diverse bacterial group ubiquitous in many soil and aquatic environments. Members of this group have been associated with human and other animal diseases, including the nontuberculous mycobacteria (NTM), which are of growing relevance to public health worldwide. Although soils are often considered an important source of environmentally acquired NTM infections, the biodiversity and ecological preferences of soil mycobacteria remain largely unexplored across contrasting climates and ecosystem types. Using a culture-independent approach by combining 16S rRNA marker gene sequencing with mycobacterium-specific hsp65 gene sequencing, we analyzed the diversity, distributions, and environmental preferences of soil-dwelling mycobacteria in 143 soil samples collected from a broad range of ecosystem types. The surveyed soils harbored highly diverse mycobacterial communities that span the full extent of the known mycobacterial phylogeny, with most soil mycobacteria (97% of mycobacterial clades) belonging to previously undescribed lineages. While mycobacteria tended to have higher relative abundances in cool, wet, and acidic soil environments, several individual mycobacterial clades had contrasting environmental preferences. We identified the environmental preferences of many mycobacterial clades, including the clinically relevant Mycobacterium avium complex that was more commonly detected in wet and acidic soils. However, most of the soil mycobacteria detected were not closely related to known pathogens, calling into question previous assumptions about the general importance of soil as a source of NTM infections. Together, this work provides novel insights into the diversity, distributions, and ecological preferences of soil mycobacteria and lays the foundation for future efforts to link mycobacterial phenotypes to their distributions.IMPORTANCE Mycobacteria are common inhabitants of soil, and while most members of this bacterial group are innocuous, some mycobacteria can cause environmentally acquired infections of humans and other animals. Human infections from nontuberculous mycobacteria (NTM) are increasingly prevalent worldwide, and some areas appear to be "hotspots" for NTM disease. While exposure to soil is frequently implicated as an important mode of NTM transmission, the diversity, distributions, and ecological preferences of soil mycobacteria remain poorly understood. We analyzed 143 soils from a range of ecosystems and found that mycobacteria and lineages within the group often exhibited predictable preferences for specific environmental conditions. Soils harbor large amounts of previously undescribed mycobacterial diversity, and lineages that include known pathogens were rarely detected in soil. Together, these findings suggest that soil is an unlikely source of many mycobacterial infections. The biogeographical patterns we documented lend insight into the ecology of this important group of soil-dwelling bacteria.

37 citations


Cited by
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01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

10,124 citations

Journal ArticleDOI
Evan Bolyen1, Jai Ram Rideout1, Matthew R. Dillon1, Nicholas A. Bokulich1, Christian C. Abnet2, Gabriel A. Al-Ghalith3, Harriet Alexander4, Harriet Alexander5, Eric J. Alm6, Manimozhiyan Arumugam7, Francesco Asnicar8, Yang Bai9, Jordan E. Bisanz10, Kyle Bittinger11, Asker Daniel Brejnrod7, Colin J. Brislawn12, C. Titus Brown5, Benjamin J. Callahan13, Andrés Mauricio Caraballo-Rodríguez14, John Chase1, Emily K. Cope1, Ricardo Silva14, Christian Diener15, Pieter C. Dorrestein14, Gavin M. Douglas16, Daniel M. Durall17, Claire Duvallet6, Christian F. Edwardson, Madeleine Ernst14, Madeleine Ernst18, Mehrbod Estaki17, Jennifer Fouquier19, Julia M. Gauglitz14, Sean M. Gibbons20, Sean M. Gibbons15, Deanna L. Gibson17, Antonio Gonzalez14, Kestrel Gorlick1, Jiarong Guo21, Benjamin Hillmann3, Susan Holmes22, Hannes Holste14, Curtis Huttenhower23, Curtis Huttenhower24, Gavin A. Huttley25, Stefan Janssen26, Alan K. Jarmusch14, Lingjing Jiang14, Benjamin D. Kaehler27, Benjamin D. Kaehler25, Kyo Bin Kang14, Kyo Bin Kang28, Christopher R. Keefe1, Paul Keim1, Scott T. Kelley29, Dan Knights3, Irina Koester14, Tomasz Kosciolek14, Jorden Kreps1, Morgan G. I. Langille16, Joslynn S. Lee30, Ruth E. Ley31, Ruth E. Ley32, Yong-Xin Liu, Erikka Loftfield2, Catherine A. Lozupone19, Massoud Maher14, Clarisse Marotz14, Bryan D Martin20, Daniel McDonald14, Lauren J. McIver23, Lauren J. McIver24, Alexey V. Melnik14, Jessica L. Metcalf33, Sydney C. Morgan17, Jamie Morton14, Ahmad Turan Naimey1, Jose A. Navas-Molina34, Jose A. Navas-Molina14, Louis-Félix Nothias14, Stephanie B. Orchanian, Talima Pearson1, Samuel L. Peoples20, Samuel L. Peoples35, Daniel Petras14, Mary L. Preuss36, Elmar Pruesse19, Lasse Buur Rasmussen7, Adam R. Rivers37, Michael S. Robeson38, Patrick Rosenthal36, Nicola Segata8, Michael Shaffer19, Arron Shiffer1, Rashmi Sinha2, Se Jin Song14, John R. Spear39, Austin D. Swafford, Luke R. Thompson40, Luke R. Thompson41, Pedro J. Torres29, Pauline Trinh20, Anupriya Tripathi14, Peter J. Turnbaugh10, Sabah Ul-Hasan42, Justin J. J. van der Hooft43, Fernando Vargas, Yoshiki Vázquez-Baeza14, Emily Vogtmann2, Max von Hippel44, William A. Walters31, Yunhu Wan2, Mingxun Wang14, Jonathan Warren45, Kyle C. Weber46, Kyle C. Weber37, Charles H. D. Williamson1, Amy D. Willis20, Zhenjiang Zech Xu14, Jesse R. Zaneveld20, Yilong Zhang47, Qiyun Zhu14, Rob Knight14, J. Gregory Caporaso1 
TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.
Abstract: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and 1565057 to R.K. Partial support was also provided by the following: grants NIH U54CA143925 (J.G.C. and T.P.) and U54MD012388 (J.G.C. and T.P.); grants from the Alfred P. Sloan Foundation (J.G.C. and R.K.); ERCSTG project MetaPG (N.S.); the Strategic Priority Research Program of the Chinese Academy of Sciences QYZDB-SSW-SMC021 (Y.B.); the Australian National Health and Medical Research Council APP1085372 (G.A.H., J.G.C., Von Bing Yap and R.K.); the Natural Sciences and Engineering Research Council (NSERC) to D.L.G.; and the State of Arizona Technology and Research Initiative Fund (TRIF), administered by the Arizona Board of Regents, through Northern Arizona University. All NCI coauthors were supported by the Intramural Research Program of the National Cancer Institute. S.M.G. and C. Diener were supported by the Washington Research Foundation Distinguished Investigator Award.

8,821 citations

Journal ArticleDOI
TL;DR: These findings guide which normalization and differential abundance techniques to use based on the data characteristics of a given study.
Abstract: Data from 16S ribosomal RNA (rRNA) amplicon sequencing present challenges to ecological and statistical interpretation. In particular, library sizes often vary over several ranges of magnitude, and the data contains many zeros. Although we are typically interested in comparing relative abundance of taxa in the ecosystem of two or more groups, we can only measure the taxon relative abundance in specimens obtained from the ecosystems. Because the comparison of taxon relative abundance in the specimen is not equivalent to the comparison of taxon relative abundance in the ecosystems, this presents a special challenge. Second, because the relative abundance of taxa in the specimen (as well as in the ecosystem) sum to 1, these are compositional data. Because the compositional data are constrained by the simplex (sum to 1) and are not unconstrained in the Euclidean space, many standard methods of analysis are not applicable. Here, we evaluate how these challenges impact the performance of existing normalization methods and differential abundance analyses. Effects on normalization: Most normalization methods enable successful clustering of samples according to biological origin when the groups differ substantially in their overall microbial composition. Rarefying more clearly clusters samples according to biological origin than other normalization techniques do for ordination metrics based on presence or absence. Alternate normalization measures are potentially vulnerable to artifacts due to library size. Effects on differential abundance testing: We build on a previous work to evaluate seven proposed statistical methods using rarefied as well as raw data. Our simulation studies suggest that the false discovery rates of many differential abundance-testing methods are not increased by rarefying itself, although of course rarefying results in a loss of sensitivity due to elimination of a portion of available data. For groups with large (~10×) differences in the average library size, rarefying lowers the false discovery rate. DESeq2, without addition of a constant, increased sensitivity on smaller datasets ( 20 samples per group) but also critically the only method tested that has a good control of false discovery rate. These findings guide which normalization and differential abundance techniques to use based on the data characteristics of a given study.

1,292 citations

Journal ArticleDOI
25 Feb 2016
TL;DR: Modification of modified 16S rRNA gene and internal transcribed spacer (ITS) primers for archaea/bacteria and fungi with nonaquatic samples demonstrated that two recently modified primer pairs that target taxonomically discriminatory regions of bacterial and fungal genomic DNA do not introduce new biases when used on a variety of sample types.
Abstract: Designing primers for PCR-based taxonomic surveys that amplify a broad range of phylotypes in varied community samples is a difficult challenge, and the comparability of data sets amplified with varied primers requires attention. Here, we examined the performance of modified 16S rRNA gene and internal transcribed spacer (ITS) primers for archaea/bacteria and fungi, respectively, with nonaquatic samples. We moved primer bar codes to the 5' end, allowing for a range of different 3' primer pairings, such as the 515f/926r primer pair, which amplifies variable regions 4 and 5 of the 16S rRNA gene. We additionally demonstrated that modifications to the 515f/806r (variable region 4) 16S primer pair, which improves detection of Thaumarchaeota and clade SAR11 in marine samples, do not degrade performance on taxa already amplified effectively by the original primer set. Alterations to the fungal ITS primers did result in differential but overall improved performance compared to the original primers. In both cases, the improved primers should be widely adopted for amplicon studies. IMPORTANCE We continue to uncover a wealth of information connecting microbes in important ways to human and environmental ecology. As our scientific knowledge and technical abilities improve, the tools used for microbiome surveys can be modified to improve the accuracy of our techniques, ensuring that we can continue to identify groundbreaking connections between microbes and the ecosystems they populate, from ice caps to the human body. It is important to confirm that modifications to these tools do not cause new, detrimental biases that would inhibit the field rather than continue to move it forward. We therefore demonstrated that two recently modified primer pairs that target taxonomically discriminatory regions of bacterial and fungal genomic DNA do not introduce new biases when used on a variety of sample types, from soil to human skin. This confirms the utility of these primers for maintaining currently recommended microbiome research techniques as the state of the art.

1,222 citations

Journal ArticleDOI
TL;DR: This Review focuses on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis.
Abstract: Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets.

992 citations