bioRxiv ScienceSearch

Biology subjects

Hou, Q.

Publications and source records attributed to Hou, Q..

2 recordsLinked to original sources

Metatranscriptome profiling of the dynamic transcription of mRNA and sRNA of a probiotic Lactobacillus strain in human gut

Metatranscriptomic sequencing has recently been applied to study how pathogens and probiotics affect human gastrointestinal (GI) tract microbiota, which provides new insights into their mechanisms of action. In this study, metatranscriptomic sequencing was applied to deduce the in vivo expression patterns of an ingested Lactobacillus casei strain, which was compared with its in vitro growth transcriptomes. Extraction of the strain-specific reads revealed that transcripts from the ingested L. casei were increased, while those from the resident L. paracasei strains remained unchanged. Mapping of all metatranscriptomic reads and transcriptomic reads to L. casei genome showed that gene expression in vitro and in vivo differed dramatically. About 39% (1163) mRNAs and 45% (93) sRNAs of L. casei well-expressed were repressed after ingested into human gut. Expression of ABC transporter genes and amino acid metabolism genes was induced at day-14 of ingestion; and genes for sugar and SCFA metabolisms were activated at day-28 of ingestion. Moreover, expression of sRNAs specific to the in vitro log phase was more likely to be activated in human gut. Expression of rli28c sRNA with peaked expression during the in vitro stationary phase was also activated in human gut; this sRNA repressed L. casei growth and lactic acid production in vitro. These findings implicate that the ingested L. casei might have to successfully change its transcription patterns to survive in human gut, and the time-dependent activation patterns indicate a highly dynamic cross-talk between the probiotic and human gut including its microbe community.\n\nImportanceProbiotic bacteria are important in food industry and as model microorganisms in understanding bacterial gene regulation. Although probiotic functions and mechanisms in human gastrointestinal tract are linked to the unique probiotic gene expression, it remains elusive how transcription of probiotic bacteria is dynamically regulated after being ingested. Previous study of probiotic gene expression in human fecal samples has been restricted due to its low abundance and the presence of of closely related species. In this study, we took the advantage of the good depth of metatranscriptomic sequencing reads and developed a strain-specific read analysis method to discriminate the transcription of the probiotic Lactobacillus casei and those of its resident relatives. This approach and additional bioinformatics analysis allowed the first study of the dynamic transcriptome profiles of probiotic L casei in vivo. The novel findings indicate a highly regulated repression and dynamic activation of probiotic genome in human GI tract.

microbiology

Combined use of procalcitonin and C-reactive protein levels can help clinically diagnose bacterial co-infections in children infected with H1N1 influenza

ObjectiveThis study evaluated the diagnostic value of measuring the levels of procalcitonin (PCT) and C-reactive protein (CRP) to differentiate children co-infected with H1N1 influenza and bacteria from children infected with H1N1 influenza alone and to provide a reliable clinical diagnostic support system with improved accuracy and precision control.\n\nMethodsConsecutive patients (children aged <5 years) with laboratory-confirmed H1N1 influenza who were hospitalized or received outpatient care from a tertiary-care hospital in Canton, China between 1 January 2012 and 1 September 2017 were included in the present study. Laboratory results, including serum PCT and CRP levels, white blood cell (WBC) counts, and blood and sputum cultures, were analyzed. The predictive value of the combination of biomarkers versus either biomarker alone for diagnosing bacterial co-infections was evaluated using logistic regression analyses.\n\nResultsOf 3180 children infected with H1N1 influenza, 226 (7.1%) met the bacterial co-infection criteria, with Staphylococcus pneumoniae being the most commonly identified bacteria (36.28%). Significantly higher PCT (1.46 vs 0.21 ng/ml, p<0.001) and CRP (19.20 vs 5.10 mg/dl, p<0.001) levels were detected in the bacterial co-infection group than in the H1N1 infection only group. Multivariate logistic regression analysis showed independent associations between PCT (odds ratio [OR]: 1.73, 95% confidence interval [CI],1.34-2.42, p<0.001) and CRP levels (OR:1.09, 95% CI, 1.06-1.13, p<0.001) with bacterial co-infections. Using PCT or CRP levels alone, the areas under the curves (AUCs) for predicting bacterial co-infections were 0.801 (95%CI, 0.772-0.855) and 0.762 (95%CI, 0.722-0.803), respectively. Using a combination of PCT and CRP, the logistic regression-based model, Logit(P)=-1.912+0.546 PCT+0.087 CRP, showed significantly greater accuracy (AUC: 0.893, 95%CI: 0.842-0.934) than did the other three biomarkers.\n\nConclusionsThe combination of PCT and CRP levels could provide a useful method of distinguishing bacterial co-infections from an H1N1 influenza infection alone in children during the early disease phase. After further validation, the flexible model derived here could assist clinicians in decision-making processes.

microbiology