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Carbonell, S.

Publications and source records attributed to Carbonell, S..

3 recordsLinked to original sources

Persistent effects of intramammary ceftiofur treatment on the gut microbiome and antibiotic resistance in dairy cattle

Intramammary (IMM) ceftiofur treatment is commonly used in dairy farms to prevent mastitis, though its impact on the cattle gut microbiome and selection of antibiotic-resistant bacteria has not been elucidated. Herein, we enrolled 40 healthy dairy cows after lactation: 20 were treated with IMM ceftiofur (Spectramast(R)DC) and a non-antibiotic internal teat sealant (bismuth subnitrate) and 20 (controls) received only bismuth subnitrate. Fecal samples were collected before (day -1) and after treatment (weeks 1, 2, 3, 5, 7, and 9) for bacterial quantification and metagenomic next-generation sequencing. Overall, 90% and 24% of the 278 samples had Gram-negative bacteria with resistance to ampicillin and ceftiofur, respectively. Most of the cows treated with ceftiofur did not have an increase in the number of resistant bacteria; however, a subset (25%) shed higher levels of ceftiofur-resistant bacteria for up to 2 weeks post-treatment. At week 5, the antibiotic-treated cows had lower microbiome abundance and richness, whereas a greater abundance of genes encoding extended-spectrum {beta}-lactamases (ESBLs), CfxA, ACI-1, and CMY, was observed at weeks 1, 5 and 9. Moreover, the contig and network analyses detected associations between {beta}-lactam resistance genes and phages, mobile genetic elements, and specific genera. Commensal bacterial populations belonging to Bacteroidetes most often possessed ESBL genes followed by members of Enterobacteriaceae. This study highlights variable, persistent effects of IMM ceftiofur treatment on the gut microbiome and resistome in dairy cattle. Antibiotic-treated cattle had an increased abundance of specific taxa and genes encoding ESBL production that persisted for 9 weeks, while fecal shedding of ESBL-producing Enterobacteriaceae varied across animals. Together, these findings highlight the need for additional studies that identify factors linked to shedding levels and the dissemination and persistence of resistance determinants on dairy farms in different geographic locations.

microbiology↗

Reference-free reconstruction and quantification of transcriptomes from long-read sequencing

Nanopore sequencing enables the efficient and unbiased measurement of transcriptomes from any sample. However, current methods for transcript identification and quantification rely of mapping reads to a reference genome, which precludes the study of species with a partial or missing reference or the identification of disease-specific transcripts not readily identifiable from a reference. Here we present RATTLE, a tool to perform reference-free reconstruction and quantification of transcripts using only Nanopore reads. Using simulated data and experimental data from isoform spike-ins, human tissues, and cell lines, we show that RATTLE accurately determines transcript sequences and their abundances, and shows good scalability with the number of transcripts. RATTLE provides unprecedented access to transcriptomes from any sample and species without relying on a reference or additional technologies.

bioinformatics↗

High-throughput annotation of full-length long noncoding RNAs with Capture Long-Read Sequencing (CLS)

Accurate annotations of genes and their transcripts is a foundation of genomics, but no annotation technique presently combines throughput and accuracy. As a result, reference gene collections remain incomplete: many gene models are fragmentary, while thousands more remain uncatalogued-particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), combining targeted RNA capture with third-generation long-read sequencing. We present an experimental re-annotation of the GENCODE intergenic lncRNA population in matched human and mouse tissues, resulting in novel transcript models for 3574 / 561 gene loci, respectively. CLS approximately doubles the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enable us to definitively characterize the genomic features of lncRNAs, including promoter- and gene-structure, and protein-coding potential. Thus CLS removes a longstanding bottleneck of transcriptome annotation, generating manual-quality full-length transcript models at high-throughput scales.\n\nAbbreviations

genomics↗