Biology subjects

Kantor, R.

Publications and source records attributed to Kantor, R..

6 recordsLinked to original sources

bioRxiv2021

Acidity and sulfur oxidation intermediate concentrations controlled by O2-driven partitioning of sulfur oxidizing bacteria in a mine tailings impoundment

Acidification of freshwater in mining impacted areas is a major global environmental problem catalyzed by sulfur-oxidizing bacteria (SOB). To date, little is known about the active bacteria in mine tailings impoundments and their environmental niches. Here, biological sulfur oxidation was investigated over four years in a mine tailings impoundment, integrating sulfur geochemistry, genome-resolved metagenomics and metatranscriptomics. We demonstrated oxygen driven niche partitioning of SOB and their metabolic pathways that explain acidity generation and thiosulfate persistence. Four chemolithoautotrophic SOB, Halothiobacillus, Thiobacillus, Sulfuricurvum and Sediminibacterium comprised 37% to 73% of the analyzed communities. The impoundment waters alternated between the dominance of Halothiobacillus versus a Thiobacillus, Halothiobacillus, Sulfuricurvum and Sediminibacterium consortia. Halothiobacillus dominance was associated with lower pH values ([~]4.3), higher [H+]/[SO42-] and lower [S2O32-], collectively indicative of extensive sulfur oxidation. Halothiobacillus, which couple sulfur oxidation via the Sox pathway to aerobic respiration or NO2- reduction, were present throughout the depth profile, yet their expression of sox genes occurred only in upper highly oxygenated waters. Conversely, when consortia of Thiobacillus, Halothiobacillus, Sulfuricurvum and Sediminibacterium dominated, recycling/disproportionating reactions were more prevalent. Thiobacillus, which dominated deeper micro-oxic/anoxic waters, oxidized sulfur primarily through the rDSR pathway, coupled to NO3-/NO2- reduction, resulting in lower [H+]/[SO42-] and higher [S2O32-] relative to upper waters. These field results mirror the Sox/rDSR-geochemical patterns of experimental SOB enrichments and reveal opportunities for biological treatments of recalcitrant reduced sulfur compounds, as well as gene-based monitoring and in situ RNA detection to predict the onset of problematic geochemistry.

microbiology↗

bioRxiv2020

Thiocyanate and organic carbon inputs drive convergent selection for specific autotrophic Afipia and Thiobacillus strains within complex microbiomes

Thiocyanate (SCN-) contamination threatens aquatic ecosystems and pollutes vital fresh water supplies. SCN- degrading microbial consortia are commercially deployed for remediation, but the impact of organic amendments on selection within SCN- degrading microbial communities has not been investigated. Here, we tested whether specific strains capable of degrading SCN- could be reproducibly selected for based on SCN- loading and the presence or absence of added organic carbon. Complex microbial communities derived from those used to treat SCN- contaminated water were exposed to systematically increased input SCN concentrations in molasses-amended and -unamended reactors and in reactors switched to unamended conditions after establishing the active SCN- degrading consortium. Five experiments were conducted over 790 days and genome-resolved metagenomics was used to resolve community composition at the strain level. A single Thiobacillus strain proliferated in all reactors at high loadings. Despite the presence of many Rhizobiales strains, a single Afipia variant dominated the molasses-free reactor at moderately high loadings. This strain is predicted to breakdown SCN- using a novel thiocyanate dehydrogenase, oxidize resulting reduced sulfur, degrade product cyanate (OCN-) to ammonia and CO2 via cyanase, and fix CO2 via the Calvin-Benson-Bassham cycle. Removal of molasses from input feed solutions reproducibly led to dominance of this strain. Neither this Afipia strain nor the thiobacilli have the capacity to produce cobalamin, a function detected in low abundance community members. Although sustained by autotrophy, reactors without molasses did not stably degrade SCN- at high loading rates, perhaps due to loss of biofilm-associated niche diversity. Overall, convergence in environmental conditions led to convergence in the strain composition, although reactor history also impacted the trajectory of community compositional change.

microbiology↗

bioRxiv2019

Analysis of unusual and signature APOBEC-mutations in HIV-1 pol next-generation sequences

IntroductionAt low mutation-detection thresholds, next generation sequencing (NGS) for HIV-1 genotypic resistance testing is susceptible to artifactual detection of mutations arising from PCR error and APOBEC-mediated G-to-A hypermutation.\n\nMethodsWe analyzed published HIV-1 pol Illumina NGS data to characterize the distribution of mutations at eight NGS thresholds: 20%, 10%, 5%, 2%, 1%, 0.5%, 0.2%, and 0.1%. At each threshold, we determined the proportion of amino acid mutations that were unusual (defined as having a prevalence <0.01% in HIV-1 group M sequences) or were signature APOBEC mutations.\n\nResultsEight studies, containing 855 samples, in the NCBI Sequence Read Archive were analyzed. As detection thresholds were lowered, there was a progressive increase in the proportion of positions with both usual and unusual mutations and in the proportion of all mutations that were unusual. The median proportion of positions with an unusual mutation increased gradually from 0% at the 20% threshold to 0.3% at the 1% threshold and then exponentially to 1.3% (0.5% threshold), 6.9% (0.2% threshold), and 23.2% (0.1% threshold). In two of three studies with available plasma HIV-1 RNA levels, the proportion of positions with unusual mutations was negatively associated with virus levels. Although the complete set of signature APOBEC mutations was much smaller than that of unusual mutations, the former outnumbered the latter in one-sixth of the samples at the 0.5%, 1%, and 2% thresholds.\n\nConclusionsThe marked increase in the proportion of positions with unusual mutations at thresholds below 1% and in samples with lower virus loads suggests that, at low thresholds, many unusual mutations are artifactual, reflecting PCR error or G-to-A hypermutation. Profiling the numbers of unusual and signature APOBEC pol mutations at different NGS thresholds may be useful to avoid selecting a threshold that is too low and poses an unacceptable risk of identifying artifactual mutations.

bioinformatics↗

bioRxiv2019

Clades of huge phage from across Earth’s ecosystems

Phage typically have small genomes and depend on their bacterial hosts for replication. DNA sequenced from many diverse ecosystems revealed hundreds of huge phage genomes, between 200 kbp and 716 kbp in length. Thirty-four genomes were manually curated to completion, including the largest phage genomes yet reported. Expanded genetic repertoires include diverse and new CRISPR-Cas systems, tRNAs, tRNA synthetases, tRNA modification enzymes, translation initiation and elongation factors, and ribosomal proteins. Phage CRISPR-Cas systems have the capacity to silence host transcription factors and translational genes, potentially as part of a larger interaction network that intercepts translation to redirect biosynthesis to phage-encoded functions. In addition, some phage may repurpose bacterial CRISPR-Cas systems to eliminate competing phage. We phylogenetically define major clades of huge phage from human and other animal microbiomes, oceans, lakes, sediments, soils and the built environment. We conclude that their large gene inventories reflect a conserved biological strategy, observed over a broad bacterial host range and across Earths ecosystems.

microbiology↗

bioRxiv2018

Hydrogen-based metabolism - An ancestral trait in lineages sibling to the Cyanobacteria

The metabolic machinery from which microbial aerobic respiration evolved is tightly linked to the origins of oxygenic Cyanobacteria (Oxyphotobacteria). Even though the majority of Oxyphotobacteria are photoautotrophs and can use carbohydrates with oxygen (O2) as the electron acceptor, all are fermenters under dark anoxic conditions. Studies suggest that the ancestor of Oxyphotobacteria may have used hydrogen (H2) as an electron donor and that two types of NiFe hydrogenases are essential for its oxidation. Melainabacteria and Sericytochromatia, close phylogenetic neighbors to Oxyphotobacteria comprise fermentative and aerobic representatives, or organisms capable of both. Margulisbacteria (candidate divisions RBX-1 and ZB3) and Saganbacteria (candidate division WOR-1), a novel cluster of bacteria phylogenetically related to Melainabacteria, Sericytochromatia and Oxyphotobacteria may further constrain the metabolic platform in which oxygenic photosynthesis and aerobic respiration arose. Here, we predict the metabolisms of Margulisbacteria and Saganbacteria from new and published metagenome-assembled genomes (MAGs) and single amplified genomes (SAGs), and compare them to their phylogenetic neighbors. Sediment-associated Margulisbacteria are predicted to have a fermentation-based metabolism featuring a variety of hydrogenases, a nitrogenase for nitrogen (N2) fixation, and electron bifurcating complexes involved in cycling of ferredoxin and NAD(P)H. Overall, the genomic features suggest the capacity for metabolic fine-tuning under strictly anoxic conditions. In contrast, the genomes of Margulisbacteria from the ocean ecosystem encode an electron transport chain that supports aerobic growth. Similarly, some Saganbacteria genomes encode various hydrogenases, and others may have the ability to use O2 under certain conditions via a putative novel type of heme copper O2 reductase. Like Melainabacteria and Sericytochromatia, Margulisbacteria and Saganbacteria have diverse energy metabolisms capable of fermentation, and aerobic or anaerobic respiration. In summary, our findings support the hypothesis that the ancestor of these groups was an anaerobe in which fermentation and H2 metabolism were central metabolic features. Our genomic data also suggests that contemporary lineages sibling to the Oxyphotobacteria may have acquired the ability to use O2 as a terminal electron acceptor under certain environmental conditions.

microbiology↗

bioRxiv2018

Measurement error and variant-calling in deep Illumina sequencing of HIV

MotivationNext-generation deep sequencing of viral genomes, particularly on the Illumina platform, is increasingly applied in HIV research. Yet, there is no standard protocol or method used by the research community to account for measurement errors that arise during sample preparation and sequencing. Correctly calling high and low frequency variants while controlling for erroneous variant calls is an important precursor to downstream interpretation, such as studying the emergence of HIV drug-resistance mutations, which in turn has clinical applications and can improve patient care.\n\nResultsWe developed a new variant-calling pipeline, hivmmer, for Illumina sequences from HIV viral genomes. First, we validated hivmmer by comparing it to other variant-calling pipelines on real HIV plasmid data sets, which have known sequences. We found that hivmmer achieves a lower rate of erroneous variant calls, and that all methods agree on the frequency of correctly called variants. Next, we compared the methods on an HIV plasmid data set that was sequenced using an amplicon-tagging protocol called Primer ID, which is designed to reduce errors and amplification bias during library preparation. We show that the Primer ID consensus does indeed have fewer erroneous variant calls compared to the variant-calling pipelines, and that hivmmer more closely approaches this low error rate compared to the other pipelines. Surprisingly, the frequency estimates from the Primer ID consensus do not differ significantly from those of the variant-calling pipelines. Finally, we built a predictive model for classifying errors in the hivmmer alignment, and show that it achieves high accuracy for identifying erroneous variant calls.\n\nAvailabilityhivmmer is freely available for non-commercial use from https://github.com/mhowison/hivmmer.\n\nContactmhowison@brown.edu

bioinformatics↗