Suboptimal bioinformatic predictions of antimicrobial resistance from whole-genome sequences in multidrug-resistant Corynebacterium isolates.

Herein, we combined different bioinformatics tools and databases (BV-BRC, ResFinder, RAST, and KmerResistance) to perform a prediction of antimicrobial resistance (AMR) in the genomic sequences of 107 Corynebacterium striatum isolates for which trustable antimicrobial susceptibility (AST) phenotypes could be retrieved. Then, the reliabilities of the AMR predictions were evaluated by different metrics: area under the ROC curve (AUC); Major Error Rates (MERs) and Very Major Error Rates (VMERs); Matthews Correlation Coefficient (MCC); F1-Score; and Accuracy. Out of 15 genes that were reliably detected in the C. striatum isolates, only tetW yielded predictive values for tetracycline resistance that were acceptable considering Food and Drug Administration (FDA)'s criteria for quality (MER < 3.0% and VMER with a 95% C.I. ≤1.5-≤7.5); this was accompanied by a MCC score higher than 0.9 for this gene. Noteworthy, our results indicate that other commonly used metrics (AUC, F1-score, and Accuracy) may render overoptimistic evaluations of AMR-prediction reliabilities on imbalanced datasets. Accordingly, out of 10 genes tested by PCR on additional multidrug-resistant Corynebacterium spp. isolates (n = 18), the tetW gene rendered the best agreement values with AST profiles (94.11%). Overall, our results indicate that genome-based AMR prediction can still be challenging for MDR clinical isolates of emerging Corynebacterium spp.

Pan-genomic analysis of Corynebacterium amycolatum gives insights into molecular mechanisms underpinning the transition to a pathogenic phenotype.

Corynebacterium amycolatum is a nonlipophilic coryneform which is increasingly being recognized as a relevant human and animal pathogen showing multidrug resistance to commonly used antibiotics. However, little is known about the molecular mechanisms involved in transition from colonization to the MDR invasive phenotype in clinical isolates. In this study, we performed a comprehensive pan-genomic analysis of C. amycolatum, including 26 isolates from different countries. We obtained the novel genome sequences of 8 of them, which are multidrug resistant clinical isolates from Spain and Tunisia. They were analyzed together with other 18 complete or draft C. amycolatum genomes retrieved from GenBank. The species C. amycolatum presented an open pan-genome (α = 0.854905), with 3,280 gene families, being 1,690 (51.52%) in the core genome, 1,121 related to accessory genes (34.17%), and 469 related to unique genes (14.29%). Although some classic corynebacterial virulence factors are absent in the species C. amycolatum, we did identify genes associated with immune evasion, toxin, and antiphagocytosis among the predicted putative virulence factors. Additionally, we found genomic evidence for extensive acquisition of antimicrobial resistance genes through genomic islands.

The pan-genome of the emerging multidrug-resistant pathogen Corynebacterium striatum.

Corynebacterium striatum, a common constituent of the human skin microbiome, is now considered an emerging multidrug-resistant pathogen of immunocompromised and chronically ill patients. However, little is known about the molecular mechanisms in the transition from colonization to the multidrug-resistant (MDR) invasive phenotype in clinical isolates. This study performed a comprehensive pan-genomic analysis of C. striatum, including isolates from "normal skin microbiome" and from MDR infections, to gain insights into genetic factors contributing to pathogenicity and multidrug resistance in this species. For this, three novel genome sequences were obtained from clinical isolates of C. striatum of patients from Brazil, and other 24 complete or draft C. striatum genomes were retrieved from GenBank, including the ATCC6940 isolate from the Human Microbiome Project. Analysis of C. striatum strains demonstrated the presence of an open pan-genome (α = 0.852803) containing 3816 gene families, including 15 antimicrobial resistance (AMR) genes and 32 putative virulence factors. The core and accessory genomes included 1297 and 1307 genes, respectively. The identified AMR genes are primarily associated with resistance to aminoglycosides and tetracyclines. Of these, 66.6% are present in genomic islands, and four AMR genes, including aac(6')-ib7, are located in a class 1-integron. In conclusion, our data indicated that C. striatum possesses genomic characteristics favorable to the invasive phenotype, with high genomic plasticity, a robust genetic arsenal for iron acquisition, and important virulence determinants and AMR genes present in mobile genetic elements.

Corynebacterium phoceense - a rare Corynebacterium species isolated from a urine sample.

Corynebacterium spp. are Gram-positive rods that are recognized to cause opportunistic diseases under certain predisposing clinical conditions. Some species have been described in urinary tract infections. In this report we document a new episode of urinary tract infection caused by Corynebacterium phoceense and describe the whole-genome sequencing, phenotypic characteristics and mass spectra obtained by matrix-assisted desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Based on genome identification and DNA-to-DNA hybridization, we can assume that our strain is the second isolate of C. phoceense to be described in a urine sample. No other infectious diseases have been reported to be associated with this species.

Recurrent COVID-19 including evidence of reinfection and enhanced severity in thirty Brazilian healthcare workers.

BACKGROUND: There is growing concern about individuals reported to suffer repeat COVID-19 disease episodes, these in a small number of cases characterised as de novo infections with distinct sequences, indicative of insufficient protective immunity even in the short term. METHODS: Observational case series and case-control studies reporting 33 cases of recurrent, symptomatic, qRT-PCR positive COVID-19. Recurrent disease was defined as symptomatic recurrence after symptom-free clinical recovery, with release from isolation >14 days from the beginning of symptoms confirmed by qRT-PCR. The case control study-design compared this group of patients with a control group of 62 patients randomly selected from the same COVID-19 database. RESULTS: Of 33 recurrent COVID-19 patients, 26 were female and 30 were HCW. Mean time to recurrence was 50.5 days which was associated with being a HCW (OR 36.4 (p <0.0001)), and blood type A (OR 4.8 (p = 0.002)). SARS-CoV-2 antibodies were signifcantly lower in recurrent patients after initial COVID-19  (2.4 ±â€¯0.610; p<0.0001) and after recurrence (6.4 ±â€¯11.34; p = 0.007).  Virus genome sequencing identified reinfection by a different isolate in one patient. CONCLUSIONS: This is the first detailed case series showing COVID-19 recurrence with qRT-PCR positivity. For one individual detection of phylogenetically distinct genomic sequences in the first and second episodes confirmed bona fide renfection, but in most cases the data do not formally distinguish between reinfection and re-emergence of a chronic infection reservoir. These episodes were significantly associated with reduced Ab response during initial disease and argue the need for ongoing vigilance without an assumption of protection after a first episode.

Ion torrent-based nasopharyngeal swab metatranscriptomics in COVID-19.

Herein, we describe the detection of a SARS-CoV-2 genome through metatranscriptome next-generation sequencing directly from the nasopharyngeal swab of a suspected case of local transmission of Covid-19, in Brazil. Depletion of human ribosomal RNA and use of an optimized in-house developed bioinformatics strategy contributed to successful detection of the virus.

Gene Expression Analysis in Bacteria by RT-qPCR.

Reverse-transcription quantitative real-time polymerase chain reaction (RT-qPCR) using fluorescent DNA-binding dyes is now a gold-standard methodology to study bacterial gene expression through relative quantitation of target mRNAs under specific experimental conditions, and recent developments in the technology allow for gene expression analysis in single cells. Nevertheless, several critical steps of the RT-qPCR protocol need to be carefully addressed in order to obtain reliable results, particularly regarding RNA sample quality and appropriate choice of reference genes. Besides, accurate reporting of study conditions is essential, as recommended by the MIQE guidelines. Herein, we provide a practical approach to quantitation of the transcript levels of bacterial genes using RT-qPCR, including a general protocol for obtaining good-quality bacterial RNA and a discussion on the selection and validation of candidate bacterial reference genes for data normalization.