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The phylum Actinobacteria includes important human pathogens like Mycobacterium tuberculosis and Corynebacterium diphtheriae and renowned producers of secondary metabolites of commercial interest, yet only a small part of its diversity is represented by sequenced genomes. Here, we present 824 actinobacterial isolate genomes in the context of a phylum-wide analysis of 6,700 genomes including public isolates and metagenome-assembled genomes (MAGs). We estimate that only 30%-50% of projected actinobacterial phylogenetic diversity possesses genomic representation via isolates and MAGs. A comparison of gene functions reveals novel determinants of host-microbe interaction as well as environment-specific adaptations such as potential antimicrobial peptides. We identify plasmids and prophages across isolates and uncover extensive prophage diversity structured mainly by host taxonomy. Analysis of >80,000 biosynthetic gene clusters reveals that horizontal gene transfer and gene loss shape secondary metabolite repertoire across taxa. Our observations illustrate the essential role of and need for high-quality isolate genome sequences.

Resource managers rely on large-scale flow and habitat enhancement actions to support sensitive species in the San Francisco Bay–Delta. The effects of these actions on target species and ecosystems are largely unknown. In 2018, we implemented an ecosystem-scale experiment to reduce salinity and improve access to high-quality habitat in Suisun Marsh, California, for Endangered Species Act-listed Delta Smelt Hypomesus transpacificus. The action included a release of approximately 46 million m3 of additional flow in conjunction with the operation of a novel water management facility, the Suisun Marsh Salinity Control Gates. This experimental action resulted in more low-salinity habitat in Suisun Marsh than would have been present as compared to similar historical low-flow summer conditions. We evaluated the effect of decreasing salinity on the species assemblage in Suisun Marsh using a combination of ordination analyses and circular statistics. We focused this analysis on long-term monitoring data collected within Suisun Marsh during July and August and found that the aquatic community changed significantly in small sloughs but not large-slough habitat in response to the Suisun Marsh action. The assemblage shift from July to August 2018 differed from historical trends in both slough sizes, albeit not significantly in large-slough habitat. Specifically, we observed (1) a shift in California bay shrimp Crangon franciscorum and Striped Bass Morone saxatilis abundance like that occurring in low-salinity, wet water year types; and (2) an uncharacteristic seasonal decline in Black Sea jellyfish Maeotias marginata. We posit that the observed community changes were driven by a combination of behavioral responses to lower-salinity conditions and physical displacement by directional flow resulting from the flow management action.

In this study, we incorporate analyses of genome-wide sequence and structural alterations with pre- and on-therapy transcriptomic and T cell repertoire features in immunotherapy-naive melanoma patients treated with immune checkpoint blockade. Although tumor mutation burden is associated with improved treatment response, the mutation frequency in expressed genes is superior in predicting outcome. Increased T cell density in baseline tumors and dynamic changes in regression or expansion of the T cell repertoire during therapy distinguish responders from non-responders. Transcriptome analyses reveal an increased abundance of B cell subsets in tumors from responders and patterns of molecular response related to expressed mutation elimination or retention that reflect clinical outcome. High-dimensional genomic, transcriptomic, and immune repertoire data were integrated into a multi-modal predictor of response. These findings identify genomic and transcriptomic characteristics of tumors and immune cells that predict response to immune checkpoint blockade and highlight the importance of pre-existing T and B cell immunity in therapeutic outcomes.

There is an extensive literature establishing, validating, and quantifying a wide range of responses of fishes to fasting. Our study complements this work by comparing fed and unfed treatments of hatchery-raised Delta Smelt (Hypomesus transpacificus)-an imperiled fish that is endemic to the San Francisco Estuary and its tributaries in California, USA-across a diverse suite of endpoints over a two-month time series. The experiment was conducted at 15.9°C, and individuals were sampled at 12 time points as starvation became increasingly severe. We found that hepatosomatic index and condition factor were relatively sensitive to starvation, becoming significantly depressed at Day 4 and 7, respectively. Histological analysis of liver showed elevated cytoplasmic inclusion bodies at Day 7, followed by increased glycogen depletion, single cell necrosis, and hydropic vacuolar degeneration at Day 14, 21, and 28, respectively. Of four antioxidants measured, glutathione decreased at Day 4, superoxide dismutase increased at Day 14, catalase increased at Day 56, and glutathione peroxidase was not affected by starvation. The net result was a ~2-fold increase in lipid peroxidation (malondialdehyde) in fasted fish that was highly inconsistent through time. RNA to DNA ratio and triglycerides in muscle were relatively insensitive to starvation, only consistently decreasing with fasting after mortality began increasing in the 'No Feeding' treatment, at Day 21. Together, these results suggest that Delta Smelt mobilize hepatic energy stores far more rapidly than lipids in muscle when subjected to fasting, leading to rapid atrophy of liver and the development of cytoplasmic inclusion bodies-possibly autophagosomes-in hepatocytes.

The Integrated Microbial Genomes & Microbiomes system v.5.0 (IMG/M: https://img.jgi.doe.gov/m/) contains annotated datasets categorized into: archaea, bacteria, eukarya, plasmids, viruses, genome fragments, metagenomes, cell enrichments, single particle sorts, and metatranscriptomes. Source datasets include those generated by the DOE's Joint Genome Institute (JGI), submitted by external scientists, or collected from public sequence data archives such as NCBI. All submissions are typically processed through the IMG annotation pipeline and then loaded into the IMG data warehouse. IMG's web user interface provides a variety of analytical and visualization tools for comparative analysis of isolate genomes and metagenomes in IMG. IMG/M allows open access to all public genomes in the IMG data warehouse, while its expert review (ER) system (IMG/MER: https://img.jgi.doe.gov/mer/) allows registered users to access their private genomes and to store their private datasets in workspace for sharing and for further analysis. IMG/M data content has grown by 60% since the last report published in the 2017 NAR Database Issue. IMG/M v.5.0 has a new and more powerful genome search feature, new statistical tools, and supports metagenome binning.

Simple Summary: This study investigates the fecal and tumor microbiome as potential biomarkers of tumor response to neoadjuvant immunotherapy in combination with chemoradiation. We performed 16S rRNA amplicon sequencing on fecal and tumor samples, as well as fecal metabolomics, on biosamples collected from patients with resectable esophageal or gastroesophageal junction carcinoma before and during treatment. The fecal microbiome of patients whose tumors achieved a pathologic complete response revealed enrichment in sphingolipid and primary bile acids, with corresponding elevated abundance of several bacterial species: Roseburis inulinivorans, Ruminococcus callidus, and Fusicantenibacter saccharivorans. While these results provide initial insight, further study is necessary to validate these data and determine how microbes alter the immune response with neoadjuvant immunotherapy. Background: Preclinical and clinical data indicate that chemoradiotherapy (CRT) in combination with checkpoint inhibitors may prime an anti-tumor immunological response in esophageal cancer. However, responses to neoadjuvant therapy can vary widely and the key biomarkers to determine response remain poorly understood. The fecal microbiome is a novel and potentially modifiable biomarker of immunotherapy response, and both fecal and tumor microbes have been found to associate with outcomes in esophageal cancer. Methods: Fecal and tumor samples were collected from patients with stage II–III resectable esophageal or gastroesophageal junction carcinoma treated with neoadjuvant immune checkpoint inhibitors (ICIs) plus CRT prior to surgical resection. Microbiome profiles were analyzed by 16S rRNA amplicon sequencing and taxonomic data were integrated with fecal metabolite analysis to assess microbial function. Results: The fecal microbiome of patients with pathological complete response (PCR) grouped in distinct clusters compared to patients with residual viable tumor (RVT) by Bray–Curtis diversity metric. Integrated taxonomic and metabolomic analysis of fecal samples identified a sphingolipid and primary bile acid as enriched in the PCR, the levels of which correlated with several bacterial species: Roseburis inulinivorans, Ruminococcus callidus, and Fusicantenibacter saccharivorans. Analysis of the tumor microbiome profiles identified several bacterial genera previously associated with esophageal tumors, including Streptococcus and Veillonella. Conclusions: These results further characterize the fecal and tumor microbiome of patients with operable esophageal cancer and identify specific microbes and metabolites that may help elucidate how microbes contribute to tumor response with neoadjuvant CRT combined with ICI. [ABSTRACT FROM AUTHOR]

Bacterial biofilms in the colon alter the host tissue microenvironment. A role for biofilms in colon cancer metabolism has been suggested but to date has not been evaluated. Using metabolomics, we investigated the metabolic influence that microbial biofilms have on colon tissues and the related occurrence of cancer. Patient-matched colon cancers and histologically normal tissues, with or without biofilms, were examined. We show the upregulation of polyamine metabolites in tissues from cancer hosts with significant enhancement of N(1), N(12)-diacetylspermine in both biofilm-positive cancer and normal tissues. Antibiotic treatment, which cleared biofilms, decreased N(1), N(12)-diacetylspermine levels to those seen in biofilm-negative tissues, indicating that host cancer and bacterial biofilm structures contribute to the polyamine metabolite pool. These results show that colonic mucosal biofilms alter the cancer metabolome to produce a regulator of cellular proliferation and colon cancer growth potentially affecting cancer development and progression.

Mucus-invasive bacterial biofilms are identified on the colon mucosa of approximately 50% of colorectal cancer (CRC) patients and approximately 13% of healthy subjects. Here, we test the hypothesis that human colon biofilms comprise microbial communities that are carcinogenic in CRC mouse models. Homogenates of human biofilm-positive colon mucosa were prepared from tumor patients (tumor and paired normal tissues from surgical resections) or biofilm-positive biopsies from healthy individuals undergoing screening colonoscopy; homogenates of biofilm-negative colon biopsies from healthy individuals undergoing screening colonoscopy served as controls. After 12 weeks, biofilm-positive, but not biofilm-negative, human colon mucosal homogenates induced colon tumor formation in 3 mouse colon tumor models (germ-free [Apc.sup.Min[DELTA]850/+]; [Il10.sup.-/-] or [Apc.sup.Min[DELTA]850/+] and specific pathogen-free [Apc.sup.Min[DELTA]716/+] mice). Remarkably, biofilm-positive communities from healthy colonoscopy biopsies induced colon inflammation and tumors similarly to biofilm-positive tumor tissues. By 1 week, biofilm-positive human tumor homogenates, but not healthy biopsies, displayed consistent bacterial mucus invasion and biofilm formation in mouse colons. 16S rRNA gene sequencing and RNA-Seq analyses identified compositional and functional microbiota differences between mice colonized with biofilm-positive and biofilm-negative communities. These results suggest human colon mucosal biofilms, whether from tumor hosts or healthy individuals undergoing screening colonoscopy, are carcinogenic in murine models of CRC., Introduction The intestinal microbiome has been implicated in a wide variety of diseases, spanning from metabolic, neurologic, and cardiovascular conditions to localized intestinal diseases, including colorectal cancer (CRC). In recent [...]

BackgroundResearch to understand and control microbiological risks associated with the consumption of fresh fruits and vegetables has examined many environments in the farm to fork continuum. An important data gap however, that remains poorly studied is the baseline description of microflora that may be associated with plant anatomy either endemically or in response to environmental pressures. Specific anatomical niches of plants may contribute to persistence of human pathogens in agricultural environments in ways we have yet to describe. Tomatoes have been implicated in outbreaks of Salmonella at least 17 times during the years spanning 1990 to 2010. Our research seeks to provide a baseline description of the tomato microbiome and possibly identify whether or not there is something distinctive about tomatoes or their growing ecology that contributes to persistence of Salmonella in this important food crop.ResultsDNA was recovered from washes of epiphytic surfaces of tomato anatomical organs; leaves, stems, roots, flowers and fruits of Solanum lycopersicum (BHN602), grown at a site in close proximity to commercial farms previously implicated in tomato-Salmonella outbreaks. DNA was amplified for targeted 16S and 18S rRNA genes and sheared for shotgun metagenomic sequencing. Amplicons and metagenomes were used to describe "native" bacterial microflora for diverse anatomical parts of Virginia-grown tomatoes.ConclusionsDistinct groupings of microbial communities were associated with different tomato plant organs and a gradient of compositional similarity could be correlated to the distance of a given plant part from the soil. Unique bacterial phylotypes (at 95% identity) were associated with fruits and flowers of tomato plants. These include Microvirga, Pseudomonas, Sphingomonas, Brachybacterium, Rhizobiales, Paracocccus, Chryseomonas and Microbacterium. The most frequently observed bacterial taxa across aerial plant regions were Pseudomonas and Xanthomonas. Dominant fungal taxa that could be identified to genus with 18S amplicons included Hypocrea, Aureobasidium and Cryptococcus. No definitive presence of Salmonella could be confirmed in any of the plant samples, although 16S sequences suggested that closely related genera were present on leaves, fruits and roots.

The assembly methods used for whole-genome shotgun (WGS) data have a major impact on the quality of resulting draft genomes. We present a novel algorithm to generate a set of "reliable" overlaps based on identifying repeat k-mers. To demonstrate the benefits of using reliable overlaps, we have created a version of the Phrap assembly program that uses only overlaps from a specific list. We call this version PhrapUMD. Integrating PhrapUMD and our "reliable-overlap" algorithm with the Baylor College of Medicine assembler, Atlas, we assemble the BACs from the Rattus norvegicus genome project. Starting with the same data as the Nov. 2002 Atlas assembly, we compare our results and the Atlas assembly to the 4.3 Mb of rat sequence in the 21 BACs that have been finished. Our version of the draft assembly of the 21 BACs increases the coverage of finished sequence from 93.4% to 96.3%, while simultaneously reducing the base error rate from 4.5 to 1.1 errors per 10,000 bases. There are a number of ways of assessing the relative merits of assemblies when the finished sequence is available. If one views the overall quality of an assembly as proportional to the inverse of the product of the error rate and sequence missed, then the assembly presented here is seven times better. The UMD Overlapper with options for reliable overlaps is available from the authors at http://www.genome.umd.edu. We also provide the changes to the Phrap source code enabling it to use only the reliable overlaps.