Influence of sequencing depth on bacterial classification and abundance in bacterial communities

Microbial diversity is the most abundant form of life. Next Generation Sequencing technologies provide the capacity to study complex bacterial communities, in which the depth and the bioinformatic tools can influence the results. In this work we explored two different protocols for bacterial classification and abundance evaluation, using 10 bacterial genomes in a simulated sample at different sequencing. Protocol A consisted of metagenome assembly with Megahit and Ray Meta and taxonomic classification with Kraken2 and Centrifuge. In protocol B only taxonomicclassification. In both protocols, rarefaction, relative abundance and beta diversity were analyzed. In the protocol A, Megahit had a mean contig length of 1,128 and Ray Meta de 8,893 nucleotides. The number of species correctly classified in all depth assays were 6 out of 10 for protocol A, and 9 out of 10 using protocol B. The rarefaction analysis showed an overestimation of the number of species in almost all assays regardless of the protocol, and the beta diversity analysis results indicated significant differences in all comparisons. Protocol A was more efficient for diversity analysis, while protocol B estimated a more precise relative abundance. Our results do not allow us to suggest an optimal sequencing depth at specie level.

Rapid uropathogen identification using surface enhanced Raman spectroscopy active filters

Urinary tract infection is one of the most common bacterial infections leading to increased morbidity, mortality and societal costs. Current diagnostics exacerbate this problem due to an inability to provide timely pathogen identification. Surface enhanced Raman spectroscopy (SERS) has the potential to overcome these issues by providing immediate bacterial classification. To date, achieving accurate classification has required technically complicated processes to capture pathogens, which has precluded the integration of SERS into rapid diagnostics. This work demonstrates that gold-coated membrane filters capture and aggregate bacteria, separating them from urine, while also providing Raman signal enhancement. An optimal gold coating thickness of 50 nm was demonstrated, and the diagnostic performance of the SERS-active filters was assessed using phantom urine infection samples at clinically relevant concentrations (105 CFU/ml). Infected and uninfected (control) samples were identified with an accuracy of 91.1%. Amongst infected samples only, classification of three bacteria (Escherichia coli, Enterococcus faecalis, Klebsiella pneumoniae) was achieved at a rate of 91.6%.

Developing bacterial set box media containing fiqh al biah for Islamic senior high school

The limitations of bacterial visualization media make bacteria consider as abstract and difficult material to study. Furthermore, the implementation of bacteria material and the integration of Islamic values are difficult to teach. This research aimed at developing and validating the BSB (Bacterial Set Box) media containing fiqh al biah. The method used in this research was R&D (Research and Development) with 4D model (Define, Design, Develop, and Disseminate) by Thiagarajan et al. The media developed was three dimensions (3D), which was packed up in a box which contained three packages. The first box was bacterial visualization; the second box was bacterial classification; the third box was 3D box containing fiqh al biah. The field test was carried out in Al Azhar Islamic Public School 16 and MA Nurussalam Semarang. The results showed that the validation percentages were 94% (material expert), 79% (media expert), 96% (integration expert), 92% (biology teacher of Al Azhar Islamic Public School 16), and 86% (biology teacher of MA Nurussalam). A pilot scale test and a large-scale test showed very feasible. It can be concluded that BSB media containing fiqh al biah is very feasible to use.

Bridging 200 years of bacterial classification.

This book chapter briefly takes a historical view of the major steps in bacterial systematics leading to the first reconciliation workshop in 1987 and a re-evaluation of the species concept in 2002. New challenges and concepts developed since then will be outlined. Never before has the future of the prokaryotic taxonomy been at such a critical point. The uncertain future, and whether Plan A or Plan B will prevail, depends totally on the wisdom of the ICSP. Perhaps by the time this book is published the situation will have been clarified, but the current situation is as full of uncertainty as of excitement, and none of the scenarios can be predicted. In April 2020, a majority of the ICSP members decided to reject the proposals to use DNA as type material. Therefore, this rejection leaves the only path for microbial ecologists to go through Plan B. Only time will reveal whether this was the best decision for the future of the taxonomy for prokaryotes.

Bacterial classification and antibiotic susceptibility testing on an integrated microfluidic platform

An ‘all in one’ digital microfluidic system is reported that automates the preparation and testing of samples for antibiotic susceptibility and bacterial classification, relying on three metabolic markers.

1216. Benchmarking Published Gene Signatures for Robust Infection Classification

Background Host gene expression has emerged as a promising diagnostic strategy to discriminate bacterial and viral infection. Multiple gene signatures of varying size and complexity have been developed in various clinical populations. However, there has been no systematic comparison of these signatures. It is also unclear how these signatures apply to different clinical populations. This meta-analysis examined 19 published signatures, validated in 49 publicly available datasets for a total of 4750 patients. The objectives were to understand how the signatures compared to each other with respect to composition and performance, and to evaluate their performance in different patient subgroups. Methods Signatures were characterized with respect to size, platform, and discovery population. For each of the 19 signatures, we ran leave-one-out cross-validation to generate AUCs for bacterial classification and viral classification. We then applied dataset-specific thresholds to generate accuracies, pooling patients across datasets. Results Signature performance varied significantly with a median AUC across all validation datasets ranging from 0.55 to 0.94 for bacterial classification and 0.79 to 0.96 for viral classification. Signature size varied (1- 341 genes) with smaller signatures generally performing more poorly for both bacterial classification (P < .001) and for viral classification (P = 0.02). Viral infection was easier to diagnose than bacterial infection (85% vs. 80% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in children < 12-years compared to those older than 12-years for both bacterial infection (77% vs. 83%, respectively; P < .001) and for viral infection (82% vs. 89%, respectively; P < .001). We did not observe differences based on illness severity as defined by ICU care for either bacterial or viral infections. Conclusion We observed significant differences among gene expression signatures for bacterial/viral discrimination, though these were not due to variations in the discovery methods or populations. Signature size directly correlated with test performance, which was generally better for the diagnosis of viral infection and in populations >12-years. Disclosures Ephraim L. Tsalik, MD, MHS, PhD, Predigen (Shareholder, Other Financial or Material Support, Founder)

Learning difficulties in comprehending virus and bacteria material for senior high schools

Previous research only focuses on the difficulties and factors causing learning difficulties without any solution. This study aimed to identify learning difficulties, factors, and alternative solutions overcoming the problems of learning difficulties about viruses and bacteria. Data collection was carried out through the provision of a concept mastery test involving 195 students (8 schools) and in-depth interviews conducted by involving 37 students (4 schools) who received the lowest test scores. Data analysis was performed using a percentage formula to determine the proportion of difficulties for each competency. The results showed that students had difficulty with the highest percentage of virus material, those were the competence of analyzing the role of viruses in life (85.64%) and virus replication process (83.21%). The competence in bacterial material which has the highest percentage of difficulty (77.26%) in identify bacterial classification. The factors causing students to have difficulty learning virus and bacteria consisted of the nature of the topic (77.03%), attitudes and learning habits (60.81%), teacher’s teaching skills (37.84%), and school facilities (27.03%). Alternative solutions are: teachers reduce the content that is complex and detailed, carry out an interactive learning process (audiovisual/animation), providing more learning experiences through practical activities, and teaching through interesting ways.