Platforms for elucidating antibiotic resistance in single genomes and complex metagenomes.
TL;DR: This review provides a detailed account of available bioinformatics platforms for identification and characterization of ARGs and associated genetic elements within single bacterial isolates and complex environmental samples, and focuses primarily on currently available ARG databases.
About: This article is published in Environment International.The article was published on 2020-05-01 and is currently open access. It has received 48 citations till now. The article focuses on the topics: Metagenomics & Population.
Citations
More filters
01 Jun 2012
TL;DR: SPAdes as mentioned in this paper is a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler and on popular assemblers Velvet and SoapDeNovo (for multicell data).
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
10,124 citations
TL;DR: Mitigating antifungal tolerance, a prelude to the emergence of resistance, also requires the development of effective and fungal-specific adjuvants to be used in combination with systemic antifundals.
Abstract: The high clinical mortality and economic burden posed by invasive fungal infections (IFIs), along with significant agricultural crop loss caused by various fungal species, has resulted in the widespread use of antifungal agents. Selective drug pressure, fungal attributes, and host- and drug-related factors have counteracted the efficacy of the limited systemic antifungal drugs and changed the epidemiological landscape of IFIs. Species belonging to Candida, Aspergillus, Cryptococcus, and Pneumocystis are among the fungal pathogens showing notable rates of antifungal resistance. Drug-resistant fungi from the environment are increasingly identified in clinical settings. Furthermore, we have a limited understanding of drug class-specific resistance mechanisms in emerging Candida species. The establishment of antifungal stewardship programs in both clinical and agricultural fields and the inclusion of species identification, antifungal susceptibility testing, and therapeutic drug monitoring practices in the clinic can minimize the emergence of drug-resistant fungi. New antifungal drugs featuring promising therapeutic profiles have great promise to treat drug-resistant fungi in the clinical setting. Mitigating antifungal tolerance, a prelude to the emergence of resistance, also requires the development of effective and fungal-specific adjuvants to be used in combination with systemic antifungals.
106 citations
TL;DR: MNGS testing of bronchoalveolar lavage fluid may be an powerful tool for early identification of potential pathogens for SCAP to initiate a precise antimicrobial therapy.
Abstract: Metagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF) has the potential to improve the pathogen identification in severe community-acquired pneumonia (SCAP). In this 1.5-year, multicenter, prospective study, we investigated the usefulness of mNGS of BALF for identifying pathogens of SCAP in hospitalized adults, comparing it with other laboratory methods. Of 329 SCAP adults, a microbial etiology was established in 304 cases (92.4%). The overall microbial yield was 90.3% for mNGS versus 39.5% for other methods (P < 0.05). The most frequently detected pathogens in immunocompetent patients were Streptococcus pneumoniae (14.8%), rhinovirus (9.8%), Haemophilus influenzae (9.1%), Staphylococcus aureus (8.7%), and Chlamydia psittaci (8.0%), while in immunocompromised patients they were Pneumocystis jirovecii (44.6%), Klebsiella pneumoniae (18.5%), Streptococcus pneumoniae (15.4%), Haemophilus influenzae (13.8%), and Pseudomonas aeruginosa (13.8%). Notably, novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified from two patients solely by mNGS in January 2020; uncommon pathogens including Orientia tsutsugamushi and Nocardia otitidiscaviarum were identified from one patient, respectively. Furthermore, mixed infections were detected in 56.8% of the patients. A high microbial detection rate was achieved in SCAP adults using mNGS testing of BALF. The most frequently detected pathogens of SCAP differed between immunocompetent and immunocompromised patients. mNGS testing may be an powerful tool for early identification of potential pathogens for SCAP to initiate a precise antimicrobial therapy.
55 citations
TL;DR: This study presents a complete ARG survey that sheds light on the distribution and fate of ARGs under heavy metal contamination in farmland around gold tailings in northern China and found that mobile gene elements had a minimal impact on ARGs.
45 citations
TL;DR: A review of the state of the art of antibiotic resistance (AR) monitoring methods, considering distinct needs, objectives and available resources, is presented in this paper, where the potential to establish reliable and useful monitoring schemes that can be implemented in distinct contexts is discussed.
41 citations
References
More filters
TL;DR: A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score.
88,255 citations
TL;DR: Burrows-Wheeler Alignment tool (BWA) is implemented, a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps.
Abstract: Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals.
Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ~10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package.
Availability: http://maq.sourceforge.net
Contact: [email protected]
43,862 citations
TL;DR: Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
Abstract: As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
37,898 citations
TL;DR: EdgeR as mentioned in this paper is a Bioconductor software package for examining differential expression of replicated count data, which uses an overdispersed Poisson model to account for both biological and technical variability and empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference.
Abstract: Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).
29,413 citations
TL;DR: Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches and can be used simultaneously to achieve even greater alignment speeds.
Abstract: Bowtie is an ultrafast, memory-efficient alignment program for aligning short DNA sequence reads to large genomes. For the human genome, Burrows-Wheeler indexing allows Bowtie to align more than 25 million reads per CPU hour with a memory footprint of approximately 1.3 gigabytes. Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches. Multiple processor cores can be used simultaneously to achieve even greater alignment speeds. Bowtie is open source http://bowtie.cbcb.umd.edu.
20,335 citations