Understanding human health through metatranscriptomics

Metatranscriptomics has revolutionized our ability to explore and understand transcriptional programs in microbial communities. Moreover, it has enabled us to gain deeper and more specific insight into the microbial activities in human gut, respiratory, oral, and vaginal communities. Perhaps the most important contribution of metatranscriptomics arises, however, from the analyses of disease-associated communities. We review the advantages and disadvantages of metatranscriptomics analyses in understanding human health and disease. We focus on human tissues low in microbial biomass and conditions associated with dysbiotic microbiota. We conclude that a more widespread use of metatranscriptomics and increased knowledge on microbe activities will uncover critical interactions between microbes and host in human health and provide diagnostic basis for culturing-independent, direct functional pathogen identification.

Blood Culture Headspace Gas Analysis Enables Early Detection of Escherichia coli Bacteremia in an Animal Model of Sepsis

(1) Background: Automated blood culture headspace analysis for the detection of volatile organic compounds of microbial origin (mVOC) could be a non-invasive method for bedside rapid pathogen identification. We investigated whether analyzing the gaseous headspace of blood culture (BC) bottles through gas chromatography-ion mobility spectrometry (GC-IMS) enables differentiation of infected and non-infected; (2) Methods: BC were gained out of a rabbit model, with sepsis induced by intravenous administration of E. coli (EC group; n = 6) and control group (n = 6) receiving sterile LB medium intravenously. After 10 h, a pair of blood cultures was obtained and incubated for 36 h. The headspace from aerobic and anaerobic BC was sampled every two hours using an autosampler and analyzed using a GC-IMS device. MALDI-TOF MS was performed to confirm or exclude microbial growth in BCs; (3) Results: Signal intensities (SI) of 113 mVOC peak regions were statistically analyzed. In 24 regions, the SI trends differed between the groups and were considered to be useful for differentiation. The principal component analysis showed differentiation between EC and control group after 6 h, with 62.2% of the data variance described by the principal components 1 and 2. Single peak regions, for example peak region P_15, show significant SI differences after 6 h in the anaerobic environment (p < 0.001) and after 8 h in the aerobic environment (p < 0.001); (4) Conclusions: The results are promising and warrant further evaluation in studies with an extended microbial panel and indications concerning its transferability to human samples.

Factors Associated With MALDI-TOF Mass Spectral Quality of Species Identification in Clinical Routine Diagnostics

Background

An accurate and timely identification of bacterial species is critical in clinical diagnostics. Species identification allows a potential first adaptation of empiric antibiotic treatments before the resistance profile is available. Matrix assisted Laser Desorption Ionization Time of Flight mass spectrometry (MALDI-TOF MS) is a widely used method for bacterial species identification. However, important challenges in species identification remain. These arise from (i) incomplete databases, (ii) close relatedness of species of interest, and (iii) spectral quality, which is currently vaguely defined.

Methods

We selected 47 clinically relevant bacterial isolates from 39 species, which can be challenging to identify by MALDI-TOF MS. We measured these isolates under various analytical conditions on two MALDI-TOF MS systems. First, we identified spectral features, which were associated with correct species identification in three different databases. Considering these features, we then systematically compared spectra produced with three different sample preparation protocols. In addition, we varied quantities of bacterial colony material applied and bacterial colony age.

Results

We identified (i) the number of ribosomal marker peaks detected, (ii) the median relative intensity of ribosomal marker peaks, (iii) the sum of the intensity of all detected peaks, (iv) a high measurement precision, and (v) reproducibility of peaks to act as good proxies of spectral quality. We found that using formic acid, measuring bacterial colonies at a young age, and frequently calibrating the MALDI-TOF MS device increase mass spectral quality. We further observed significant differences in spectral quality between different bacterial taxa and optimal measurement conditions vary per taxon.

Conclusion

We identified and applied quality measures for MALDI-TOF MS and optimized spectral quality in routine settings. Phylogenetic marker peaks can be reproducibly detected and provide an increased resolution and the ability to distinguish between challenging species such as those within the Enterobacter cloacae complex, Burkholderia cepacia complex, or viridans streptococci.