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1. Results from a multi-laboratory ocean metaproteomic intercomparison: effects of LC-MS acquisition and data analysis procedures

   https://doi.org/10.5194/bg-21-4889-2024  

   Saito, Mak A; Saunders, Jaclyn K; McIlvin, Matthew R; Bertrand, Erin M; Breier, John A; Brisbin, Margaret Mars; Colston, Sophie M; Compton, Jaimee R; Griffin, Tim J; Hervey, W Judson; et al (January 2024, Biogeosciences)

   Abstract. Metaproteomics is an increasingly popular methodology that provides information regarding the metabolic functions of specific microbial taxa and has potential for contributing to ocean ecology and biogeochemical studies. A blinded multi-laboratory intercomparison was conducted to assess comparability and reproducibility of taxonomic and functional results and their sensitivity to methodological variables. Euphotic zone samples from the Bermuda Atlantic Time-series Study (BATS) in the North Atlantic Ocean collected by in situ pumps and the autonomous underwater vehicle (AUV) Clio were distributed with a paired metagenome, and one-dimensional (1D) liquid chromatographic data-dependent acquisition mass spectrometry analysis was stipulated. Analysis of mass spectra from seven laboratories through a common bioinformatic pipeline identified a shared set of 1056 proteins from 1395 shared peptide constituents. Quantitative analyses showed good reproducibility: pairwise regressions of spectral counts between laboratories yielded R2 values averaged 0.62±0.11, and a Sørensen similarity analysis of the top 1000 proteins revealed 70 %–80 % similarity between laboratory groups. Taxonomic and functional assignments showed good coherence between technical replicates and different laboratories. A bioinformatic intercomparison study, involving 10 laboratories using eight software packages, successfully identified thousands of peptides within the complex metaproteomic datasets, demonstrating the utility of these software tools for ocean metaproteomic research. Lessons learned and potential improvements in methods were described. Future efforts could examine reproducibility in deeper metaproteomes, examine accuracy in targeted absolute quantitation analyses, and develop standards for data output formats to improve data interoperability. Together, these results demonstrate the reproducibility of metaproteomic analyses and their suitability for microbial oceanography research, including integration into global-scale ocean surveys and ocean biogeochemical models. 

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2. Metaproteomics as a tool for studying the protein landscape of human-gut bacterial species

   https://doi.org/10.1371/journal.pcbi.1009397  

   Stamboulian, Moses; Canderan, Jamie; Ye, Yuzhen (March 2022, PLOS Computational Biology)

   Coelho, Luis Pedro (Ed.)

   Host-microbiome interactions and the microbial community have broad impact in human health and diseases. Most microbiome based studies are performed at the genome level based on next-generation sequencing techniques, but metaproteomics is emerging as a powerful technique to study microbiome functional activity by characterizing the complex and dynamic composition of microbial proteins. We conducted a large-scale survey of human gut microbiome metaproteomic data to identify generalist species that are ubiquitously expressed across all samples and specialists that are highly expressed in a small subset of samples associated with a certain phenotype. We were able to utilize the metaproteomic mass spectrometry data to reveal the protein landscapes of these species, which enables the characterization of the expression levels of proteins of different functions and underlying regulatory mechanisms, such as operons. Finally, we were able to recover a large number of open reading frames (ORFs) with spectral support, which were missed by de novo protein-coding gene predictors. We showed that a majority of the rescued ORFs overlapped with de novo predicted protein-coding genes, but on opposite strands or in different frames. Together, these demonstrate applications of metaproteomics for the characterization of important gut bacterial species. 

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3. Breaking Barriers with Bread: Using the Sourdough Starter Microbiome to Teach High-Throughput Sequencing Techniques

   https://doi.org/10.1128/jmbe.00306-21  

   Holt, Benjamin H.; Buchan, Alison; DeBruyn, Jennifer M.; Goodrich-Blair, Heidi; McPherson, Elizabeth; Brown, Veronica A. (August 2022, Journal of Microbiology & Biology Education)

   Westenberg, Dave J. (Ed.)

   ABSTRACT Widespread usage of high-throughput sequencing (HTS) in the LIFE SCIENCES has produced a demand for undergraduate and graduate institutions to offer classes exposing students to all aspects of HTS (sample acquisition, laboratory work, sequencing technologies, bioinformatics, and statistical analyses). Despite the increase in demand, many challenges exist for these types of classes. We advocate for the usage of the sourdough starter microbiome for implementing meta-amplicon sequencing. The relatively small community, dominated by a few taxa, enables potential contaminants to be easily identified, while between-sample differences can be quickly statistically assessed. Finally, bioinformatic pipelines and statistical analyses can be carried out on personal student laptops or in a teaching computer lab. In two semesters adopting this system, 12 of 14 students were able to effectively capture the sourdough starter microbiome, using the instructor’s paired sample as reference. 

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4. Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution

   https://doi.org/10.1038/s41396-021-01178-4  

   Bowers, Robert M.; Nayfach, Stephen; Schulz, Frederik; Jungbluth, Sean P.; Ruhl, Ilona A.; Sheremet, Andriy; Lee, Janey; Goudeau, Danielle; Eloe-Fadrosh, Emiley A.; Stepanauskas, Ramunas; et al (May 2022, The ISME Journal)

   Abstract With advances in DNA sequencing and miniaturized molecular biology workflows, rapid and affordable sequencing of single-cell genomes has become a reality. Compared to 16S rRNA gene surveys and shotgun metagenomics, large-scale application of single-cell genomics to whole microbial communities provides an integrated snapshot of community composition and function, directly links mobile elements to their hosts, and enables analysis of population heterogeneity of the dominant community members. To that end, we sequenced nearly 500 single-cell genomes from a low diversity hot spring sediment sample from Dewar Creek, British Columbia, and compared this approach to 16S rRNA gene amplicon and shotgun metagenomics applied to the same sample. We found that the broad taxonomic profiles were similar across the three sequencing approaches, though several lineages were missing from the 16S rRNA gene amplicon dataset, likely the result of primer mismatches. At the functional level, we detected a large array of mobile genetic elements present in the single-cell genomes but absent from the corresponding same species metagenome-assembled genomes. Moreover, we performed a single-cell population genomic analysis of the three most abundant community members, revealing differences in population structure based on mutation and recombination profiles. While the average pairwise nucleotide identities were similar across the dominant species-level lineages, we observed differences in the extent of recombination between these dominant populations. Most intriguingly, the creek’s Hydrogenobacter sp . population appeared to be so recombinogenic that it more closely resembled a sexual species than a clonally evolving microbe. Together, this work demonstrates that a randomized single-cell approach can be useful for the exploration of previously uncultivated microbes from community composition to population structure. 

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5. Implementing community best practice data and metadata capture into laboratory workflows using Sparrow

   Kuehn, S.C. (January 2022, EarthCube Annual Meeting 2022)

   An implementation of the Sparrow data system (https://sparrow-data.org) is currently being developed to support laboratory workflows for sample preparation, geochemical analysis, and SEM imaging in support of tephra research. Tephra, consisting of fragmental material ejected from volcanoes, has a multidisciplinary array of applications from volcanology to geochronology, archaeology, environmental change, and more. The international tephra research community has developed a comprehensive set of recommendations for data and metadata collection and reporting (https://doi.org/10.5281/zenodo.3866266) as part of a broader effort to adopt FAIR practices. Implementations of these recommendations now exist for field data via StraboSpot (https://strabospot.org/files/StraboSpotTephraHelp.pdf) and for samples, analytical methods, and geochemistry via SESAR and EarthChem (https://earthchem.org/communities/tephra/). Implementing these recommended practices in Sparrow helps to (1) cover laboratory workflows between field sample collection and project data archiving and (2) address a key researcher pain point. As re-emphasized by participants in the Tephra Fusion 2022 workshop earlier this year (Wallace et al., this meeting), the huge workload currently needed to capture and organize data and metadata in preparation for archiving in community data repositories is a major obstacle to achieving FAIR practices. By capturing this information on the fly during laboratory workflows and integrating it together in a single data system, this challenge may be overcome. We are implementing the tephra community recommendations as extensions to Sparrow’s core database schema. Data import pipelines and user interfaces to streamline metadata capture are also being developed. In the longer term, we aim to achieve interoperability with an ecosystem of tools and repositories like StraboSpot, SESAR, EarthChem, and Throughput. The results of these developments will be applicable not just to tephra but also to other research areas which utilize similar laboratory and analytical methods - e.g. sedimentology, mineralogy, and petrology. 

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