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Belda-Ferre, P.

Publications and source records attributed to Belda-Ferre, P..

8 recordsLinked to original sources

Direct In-Sample Sequencing of the 3' Transcriptome Expands the Capabilities of Optical Pooled Screens

We present a platform that directly sequences single guide RNAs and endogenous 3'UTRs in fixed cells while simultaneously measuring protein abundance and cellular morphology. We demonstrate platform capability by performing optical pooled screening of CRISPR-perturbed lung cancer cells. This approach unites direct in-sample RNA sequencing with complementary phenotypic readouts, enabling comprehensive, scalable, and functional genomics analyses within a single experiment.

genomics↗

Pathogenic Bacteroides fragilis strains can emerge from gut-resident commensals

Bacteroides fragilis is a prominent member of the human gut microbiota, playing crucial roles in maintaining gut homeostasis and host health. Although it primarily functions as a beneficial commensal, B. fragilis can become pathogenic. To determine the genetic basis of its duality, we conducted a comparative genomic analysis of 813 B. fragilis strains, representing both commensal and pathogenic origins. Our findings reveal that pathogenic strains emerge across diverse phylogenetic lineages, due in part to rapid gene exchange and the adaptability of the accessory genome. We identified 16 phylogenetic groups, differentiated by genes associated with capsule composition, interspecies competition, and host interactions. A microbial genome-wide association study identified 44 genes linked to extra-intestinal survival and pathogenicity. These findings reveal how genomic diversity within commensal species can lead to the emergence of pathogenic traits, broadening our understanding of microbial evolution in the gut.

microbiology↗

Sentinel Cards Provide Practical SARS-CoV-2 Monitoring in School Settings

Accurate, high-resolution environmental monitoring of SARS-CoV-2 traces indoors through sentinel cards is a promising approach to help students safely return to in-person learning. Because SARS-CoV-2 RNA can persist for up to a week on several indoor surface types, there is a need for increased temporal resolution to determine whether consecutive surface positives arise from new infection events or continue to report past events. Cleaning sentinel cards after sampling would provide the needed resolution, but might interfere with assay performance. We tested the effect of three cleaning solutions (BZK wipes, wet wipes, RNase Away) at three different viral loads: "high" (4 x 104 GE/mL), "medium" (1 x 104 GE/mL), and "low" (2.5 x 103 GE/mL). RNAse Away, chosen as a positive control, was the most effective cleaning solution on all three viral loads. Wet wipes were found to be more effective than BZK wipes in the medium viral load condition. The low viral load condition was easily reset with all three cleaning solutions. These findings will enable temporal SARS-CoV-2 monitoring in indoor environments where transmission risk of the virus is high and the need to avoid individual-level sampling for privacy or compliance reasons exists. ImportanceBecause SARS-CoV-2, the virus that causes COVID-19, persists on surfaces, testing swabs taken from surfaces is useful as a monitoring tool. This approach is especially valuable in school settings, where there are cost and privacy concerns that are eliminated by taking a single sample from a classroom. However, the virus persists for days to weeks on surface samples, so it is impossible to tell whether positive detection events on consecutive days are persistent signal or new infectious cases, and therefore whether the positive individuals have been successfully removed from the classroom. We compare several methods for cleaning "sentinel cards" to show that this approach can be used to identify new SARS-CoV-2 signals day to day. The results are important for determining how to monitor classrooms and other indoor environments for SARS-CoV-2 virus.

bioinformatics↗

Comparison of heat-inactivated and infectious SARS-CoV-2 across indoor surface materials shows comparable RT-qPCR viral signal intensity and persistence

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with COVID-19 and inform appropriate infection mitigation responses. Research groups have reported detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2 positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over seven days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle (Cq)) can be correlated to surface viral load using only one linear regression model per material category. The same experiment was performed with infectious viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. ImportanceEnvironmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made towards containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) [1], a large-scale environmental monitoring effort in elementary school and child care settings, has processed > 13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT - qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.

microbiology↗

OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures

We introduce Operational Genomic Unit (OGU), a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent from taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldomly applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in one synthetic and two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome datasets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project dataset, and more accurate prediction of human age by the gut microbiomes in the Finnish population. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate OGU adoption in future metagenomics studies. ImportanceShotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. However, current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution compared to 16S rRNA amplicon sequence variant analysis. To solve these challenges, we introduce Operational Genomic Units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition while (ii) permitting use of phylogeny-aware tools. Our analysis of real-world datasets shows several advantages over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGU as standard practice in metagenomic studies.

bioinformatics↗

A comparison of DNA/RNA extraction protocols for high-throughput sequencing of microbial communities

One goal among microbial ecology researchers is to capture the maximum amount of information from all organisms in a sample. The recent COVID-19 pandemic, caused by the RNA virus SARS-CoV-2, has highlighted a gap in traditional DNA-based protocols, including the high-throughput methods we previously established as field standards. To enable simultaneous SARS-CoV-2 and microbial community profiling, we compare the relative performance of two total nucleic acid extraction protocols and our previously benchmarked protocol. We included a diverse panel of environmental and host-associated sample types, including body sites commonly swabbed for COVID-19 testing. Here we present results comparing the cost, processing time, DNA and RNA yield, microbial community composition, limit of detection, and well-to-well contamination, between these protocols. Accession numbersRaw sequence data were deposited at the European Nucleotide Archive (accession#: ERP124610) and raw and processed data are available at Qiita (Study ID: 12201). All processing and analysis code is available on GitHub (github.com/justinshaffer/Extraction_test_MagMAX). Methods summaryTo allow for downstream applications involving RNA-based organisms such as SARS-CoV-2, we compared the two extraction protocols designed to extract DNA and RNA against our previously established protocol for extracting only DNA for microbial community analyses. Across 10 diverse sample types, one of the two protocols was equivalent or better than our established DNA-based protocol. Our conclusion is based on per-sample comparisons of DNA and RNA yield, the number of quality sequences generated, microbial community alpha- and beta-diversity and taxonomic composition, the limit of detection, and extent of well-to-well contamination.

ecology↗

Bacterial modification of the host glycosaminoglycan heparan sulfate modulates SARS-CoV-2 infectivity

The human microbiota has a close relationship with human disease and it remodels components of the glycocalyx including heparan sulfate (HS). Studies of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) spike protein receptor binding domain suggest that infection requires binding to HS and angiotensin converting enzyme 2 (ACE2) in a codependent manner. Here, we show that commensal host bacterial communities can modify HS and thereby modulate SARS-CoV-2 spike protein binding and that these communities change with host age and sex. Common human-associated commensal bacteria whose genomes encode HS-modifying enzymes were identified. The prevalence of these bacteria and the expression of key microbial glycosidases in bronchoalveolar lavage fluid (BALF) was lower in adult COVID-19 patients than in healthy controls. The presence of HS-modifying bacteria decreased with age in two large survey datasets, FINRISK 2002 and American Gut, revealing one possible mechanism for the observed increase in COVID-19 susceptibility with age. In vitro, bacterial glycosidases from unpurified culture media supernatants fully blocked SARS-CoV-2 spike binding to human H1299 protein lung adenocarcinoma cells. HS-modifying bacteria in human microbial communities may regulate viral adhesion, and loss of these commensals could predispose individuals to infection. Understanding the impact of shifts in microbial community composition and bacterial lyases on SARS-CoV-2 infection may lead to new therapeutics and diagnosis of susceptibility. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/238444v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@14ff1ecorg.highwire.dtl.DTLVardef@193d84corg.highwire.dtl.DTLVardef@15d6f9eorg.highwire.dtl.DTLVardef@14b16c6_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract. Diagram of hypothesis for bacterial mediation of SARS-CoV-2 infection through heparan sulfate (HS).It is well known that host microbes groom the mucosa where they reside. Recent investigations have shown that HS, a major component of mucosal layers, is necessary for SARS-CoV-2 infection. In this study we examine the impact of microbial modification of HS on viral attachment. C_FIG

microbiology↗

Ultra-low input single tube linked-read library method enables short-read NGS systems to generate highly accurate and economical long-range sequencing information for de novo genome assembly and haplotype phasing

Long-range sequencing information is required for haplotype phasing, de novo assembly and structural variation detection. Current long-read sequencing technologies can provide valuable long-range information but at a high cost with low accuracy and high DNA input requirement. We have developed a single-tube Transposase Enzyme Linked Long-read Sequencing (TELL-Seq) technology, which enables a low-cost, high-accuracy and high-throughput short-read next generation sequencer to routinely generate over 100 Kb long-range sequencing information with as little as 0.1 ng input material. In a PCR tube, millions of clonally barcoded beads are used to uniquely barcode long DNA molecules in an open bulk reaction without dilution and compartmentation. The barcode linked reads are used to successfully assemble genomes ranging from microbes to human. These linked-reads also generate mega-base-long phased blocks and provide a cost-effective tool for detecting structural variants in a genome, which are important to identify compound heterozygosity in recessive Mendelian diseases and discover genetic drivers and diagnostic biomarkers in cancers.

genomics↗