Reference-free Structural Variant Detection in Microbiomes via Long-read Coassembly Graphs.

Bacterial genome dynamics are vital for understanding the mechanisms underlying microbial adaptation, growth, and their broader impact on host phenotype. Structural variants (SVs), genomic alterations of 10 base pairs or more, play a pivotal role in driving evolutionary processes and maintaining genomic heterogeneity within bacterial populations. While SV detection in isolate genomes is relatively straightforward, metagenomes present broader challenges due to absence of clear reference genomes and presence of mixed strains. In response, our proposed method rhea, forgoes reference genomes and metagenome-assembled genomes (MAGs) by encompassing a single metagenome coassembly graph constructed from all samples in a series. The log fold change in graph coverage between subsequent samples is then calculated to call SVs that are thriving or declining throughout the series. We show rhea to outperform existing methods for SV and horizontal gene transfer (HGT) detection in two simulated mock metagenomes, which is particularly noticeable as the simulated reads diverge from reference genomes and an increase in strain diversity is incorporated. We additionally demonstrate use cases for rhea on series metagenomic data of environmental and fermented food microbiomes to detect specific sequence alterations between subsequent time and temperature samples, suggesting host advantage. Our innovative approach leverages raw read patterns rather than references or MAGs to include all sequencing reads in analysis, and thus provide versatility in studying SVs across diverse and poorly characterized microbial communities for more comprehensive insights into microbial genome dynamics.

Gastrointestinal symptoms and fecal shedding of SARS-CoV-2 RNA suggest prolonged gastrointestinal infection.

Background: COVID-19 manifests with respiratory, systemic, and gastrointestinal (GI) symptoms.1, SARS-CoV-2 RNA is detected in respiratory and fecal samples, and recent reports demonstrate viral replication in both the lung and intestinal tissue.2, 3, 4 Although much is known about early fecal RNA shedding, little is known about long-term shedding, especially in those with mild COVID-19. Furthermore, most reports of fecal RNA shedding do not correlate these findings with GI symptoms.5. Methods: We analyzed the dynamics of fecal RNA shedding up to 10 months after COVID-19 diagnosis in 113 individuals with mild to moderate disease. We also correlated shedding with disease symptoms. Findings: Fecal SARS-CoV-2 RNA is detected in 49.2% [95% confidence interval, 38.2%-60.3%] of participants within the first week after diagnosis. Whereas there was no ongoing oropharyngeal SARS-CoV-2 RNA shedding in subjects at 4 months, 12.7% [8.5%-18.4%] of participants continued to shed SARS-CoV-2 RNA in the feces at 4 months after diagnosis and 3.8% [2.0%-7.3%] shed at 7 months. Finally, we found that GI symptoms (abdominal pain, nausea, vomiting) are associated with fecal shedding of SARS-CoV-2 RNA. Conclusions: The extended presence of viral RNA in feces, but not in respiratory samples, along with the association of fecal viral RNA shedding with GI symptoms suggest that SARS-CoV-2 infects the GI tract and that this infection can be prolonged in a subset of individuals with COVID-19. Funding: This research was supported by a Stanford ChemH-IMA grant; fellowships from the AACR and NSF; and NIH R01-AI148623, R01-AI143757, and UL1TR003142.

Identification of covalent inhibitors that disrupt M. tuberculosis growth by targeting multiple serine hydrolases involved in lipid metabolism.

The increasing incidence of antibiotic-resistant Mycobacterium tuberculosis infections is a global health threat necessitating the development of new antibiotics. Serine hydrolases (SHs) are a promising class of targets because of their importance for the synthesis of the mycobacterial cell envelope. We screen a library of small molecules containing serine-reactive electrophiles and identify narrow-spectrum inhibitors of M. tuberculosis growth. Using these lead molecules, we perform competitive activity-based protein profiling and identify multiple SH targets, including enzymes with uncharacterized functions. Lipidomic analyses of compound-treated cultures reveal an accumulation of free lipids and a substantial decrease in lipooligosaccharides, linking SH inhibition to defects in cell envelope biogenesis. Mutant analysis reveals a path to resistance via the synthesis of mycocerates, but not through mutations to SH targets. Our results suggest that simultaneous inhibition of multiple SH enzymes is likely to be an effective therapeutic strategy for the treatment of M. tuberculosis infections.

Standardized preservation, extraction and quantification techniques for detection of fecal SARS-CoV-2 RNA.

Patients with COVID-19 shed SARS-CoV-2 RNA in stool, sometimes well after their respiratory infection has cleared. This may be significant for patient health, epidemiology, and diagnosis. However, methods to preserve stool, and to extract and quantify viral RNA are not standardized. We test the performance of three preservative approaches at yielding detectable SARS-CoV-2 RNA: the OMNIgene-GUT kit, Zymo DNA/RNA shield kit, and the most commonly applied, storage without preservative. We test these in combination with three extraction kits: QIAamp Viral RNA Mini Kit, Zymo Quick-RNA Viral Kit, and MagMAX Viral/Pathogen Kit. We also test the utility of ddPCR and RT-qPCR for the reliable quantification of SARS-CoV-2 RNA from stool. We identify that the Zymo DNA/RNA preservative and the QiaAMP extraction kit yield more detectable RNA than the others, using both ddPCR and RT-qPCR. Taken together, we recommend a comprehensive methodology for preservation, extraction and detection of RNA from SARS-CoV-2 and other coronaviruses in stool.

Standardized and optimized preservation, extraction and quantification techniques for detection of fecal SARS-CoV-2 RNA.

COVID-19 patients shed SARS-CoV-2 viral RNA in their stool, sometimes well after they have cleared their respiratory infection. This feature of the disease may be significant for patient health, epidemiology, and diagnosis. However, to date, methods to preserve stool samples from COVID patients, and to extract and quantify viral RNA concentration have yet to be optimized. We sought to meet this urgent need by developing and benchmarking a standardized protocol for the fecal detection of SARS-CoV-2 RNA. We test three preservative conditions for their ability to yield detectable SARS-CoV-2 RNA: OMNIgene-GUT, Zymo DNA/RNA shield kit, and the most common condition, storage without any preservative. We test these in combination with three extraction kits: the QIAamp Viral RNA Mini Kit, Zymo Quick-RNA Viral Kit, and MagMAX Viral/Pathogen Kit. Finally, we also test the utility of two detection methods, ddPCR and RT-qPCR, for the robust quantification of SARS-CoV-2 viral RNA from stool. We identify that the Zymo DNA/RNA shield collection kit and the QiaAMP viral RNA mini kit yield more detectable RNA than the others, using both ddPCR and RT-qPCR assays. We also demonstrate key features of experimental design including the incorporation of appropriate controls and data analysis, and apply these techniques to effectively extract viral RNA from fecal samples acquired from COVID-19 outpatients enrolled in a clinical trial. Finally, we recommend a comprehensive methodology for future preservation, extraction and detection of RNA from SARS-CoV-2 and other coronaviruses in stool.

Improved high-molecular-weight DNA extraction, nanopore sequencing and metagenomic assembly from the human gut microbiome.

Short-read metagenomic sequencing and de novo genome assembly of the human gut microbiome can yield draft bacterial genomes without isolation and culture. However, bacterial genomes assembled from short-read sequencing are often fragmented. Furthermore, these metagenome-assembled genomes often exclude repeated genomic elements, such as mobile genetic elements, compromising our understanding of the contribution of these elements to important bacterial phenotypes. Although long-read sequencing has been applied successfully to the assembly of contiguous bacterial isolate genomes, extraction of DNA of sufficient molecular weight, purity and quantity for metagenomic sequencing from stool samples can be challenging. Here, we present a protocol for the extraction of microgram quantities of high-molecular-weight DNA from human stool samples that are suitable for downstream long-read sequencing applications. We also present Lathe ( www.github.com/bhattlab/lathe ), a computational workflow for long-read basecalling, assembly, consensus refinement with long reads or Illumina short reads and genome circularization. Altogether, this protocol can yield high-quality contiguous or circular bacterial genomes from a complex human gut sample in approximately 10 d, with 2 d of hands-on bench and computational effort.