Rapid identification of bacterial mixtures in urine using MALDI-TOF MS-based algorithm profiling coupled with magnetic enrichment

Urinary tract infections (UTIs) are severe public health problem and caused by mono- or poly-bacteria. Culture-based methods are routinely used for the diagnosis of UTIs in clinical practice, but those...

Rapid profiling of drug-resistant bacteria using DNA-binding dyes and a nanopore-based DNA sequencer

Spread of drug-resistant bacteria is a serious problem worldwide. We thus designed a new sequence-based protocol that can quickly identify bacterial compositions of clinical samples and their drug-resistance profiles simultaneously. Here we utilized propidium monoazide (PMA) that prohibits DNA amplifications from dead bacteria, and subjected the original and antibiotics-treated samples to 16S rRNA metagenome sequencing. We tested our protocol on bacterial mixtures, and observed that sequencing reads derived from drug-resistant bacteria were significantly increased compared with those from drug-sensitive bacteria when samples were treated by antibiotics. Our protocol is scalable and will be useful for quickly profiling drug-resistant bacteria.

Rapid profiling of drug-resistant bacteria using DNA-binding dyes and a nanopore-based DNA sequencer

Spread of drug-resistant bacteria is a serious problem worldwide. We thus designed a new sequence-based protocol that can quickly identify bacterial compositions of clinical samples and their drug-resistance profiles simultaneously. Here we utilized propidium monoazide (PMA) that prohibits DNA amplifications from dead bacteria, and subjected the original and antibiotics-treated samples to 16S rRNA metagenome sequencing. We tested our protocol on bacterial mixtures, and observed that sequencing reads derived from drug-resistant bacteria were significantly increased compared with those from drug-sensitive bacteria when samples were treated by antibiotics. Our protocol is scalable and will be useful for quickly profiling drug-resistant bacteria.

Integrated metabolome and transcriptome analyses provide insight into colon cancer development by the gut microbiota

Colon cancer onset and progression is strongly associated with the presence, absence, or differences in relative abundances of certain microbial taxa in the gastrointestinal tract. However, specific mechanisms affecting disease susceptibility related to complex commensal bacterial mixtures are poorly understood. We used a multi-omics approach to determine how differences in the complex gut microbiome (GM) influence the metabolome and host transcriptome and ultimately affect susceptibility to adenoma development in a preclinical rat model of colon cancer. Fecal samples from rats harboring distinct complex GMs were analyzed using ultra-high performance liquid chromatography mass spectrometry (UHPLC-MS). We collected samples prior to observable disease onset and identified putative metabolite profiles that predicted future disease severity, independent of GM status. Transcriptome analyses performed after disease onset from normal epithelium and tumor tissues between the high and low tumor GMs suggests that the GM is correlated with altered host gene expression. Integrated pathway (IP) analyses of the metabolome and transcriptome based on putatively identified metabolic features indicate that bile acid biosynthesis was enriched in rats with high tumors (GM:F344) along with increased fatty acid metabolism and mucin biosynthesis. These data emphasize the utility of using untargeted metabolomics to reveal signatures of susceptibility and resistance and integrated analyses to reveal common pathways that are likely to be universal targets for intervention.Statement of significanceFecal metabolites, influenced by the gut microbiota, correlate with colon adenoma risk in a preclinical model of familial colon cancer.

BIOLOGICAL CONTROL: ISOLATED AND IN MIXTURES AND GENETIC CONTROL OF Meloidogyne exigua IN COFFE

<em>Meloidogyne exigua</em> is one of the most found species of nematodes in coffee plantations in the Brazilian Cerrado. Thus, the objective of the present study was to evaluate the efficiency of biological agents on two coffee cultivars. The experiment was carried out in a greenhouse using a completely randomized design. The treatments were arranged in a 2x3 factorial scheme, using repeated measures (two cultivars, 3 nematicides, and 2 additional controls), and were composed of two genotypes (Mundo Novo IAC 376-4 and IPR-100), three biological nematicides (B. methylotrophicus, B. subitilis, and T. asperellum), and two treatments including the three nematicides together, totaling 8 treatments and 2 controls, with 6 replicates each. The plants were inoculated with 3,780 eggs and J2s of the respective nematode. Throughout 150 days, the following variables were evaluated monthly: plant height, stem diameter, number of leaf pairs, and chlorophyll contents. At the end of this period (DAI), the reproductive factor (RF), egg mass and gall index were analyzed. About FR, the results were lower (&lt;1) when using the cultivar IPR-100 when compared to the Mundo Novo genotype, denoting adequate genetic control. On the other hand, in the treatments with the susceptible genotype, high FRs were verified, ranging from 2.64 to 5.68 in the control. It was concluded that the bacterial mixtures were efficient in the control, and B.<em> methylotrophicus</em> contributed to higher plant height in the IPR 100 genotype.

Speed, accuracy, sensitivity and quality control choices for detecting clinically relevant microbes in whole blood from patients

ABSTRACTInfections are a serious health concern worldwide, particularly in vulnerable populations such as the immunocompromised, elderly, and young. Advances in metagenomic sequencing availability, speed, and decreased cost offer the opportunity to supplement or replace culture-based identification of pathogens with DNA sequence-based diagnostics. Adopting metagenomic analysis for clinical use requires that all aspects of the pipeline are optimized and tested, including data analysis. We tested the accuracy, sensitivity, and resource requirements of Centrifuge within the context of clinically relevant bacteria. Binary mixtures of bacteria showed Centrifuge reliably identified organisms down to 0.1% relative abundance. A staggered mock bacterial community showed Centrifuge outperformed CLARK while requiring less computing resources. Shotgun metagenomes obtained from whole blood in three febrile neutropenia patients showed Centrifuge could identify both bacteria and viruses as part of a culture-free workflow. Finally, Centrifuge results changed minimally by eliminating time-consuming read quality control and host screening steps.AUTHOR SUMMARYImmunocompromised patients, such as those with febrile neutropenia (FN), are susceptible to infections, yet cultures fail to identify causative organisms ~80% of the time. High-throughput metagenomic sequencing offers a promising approach for identifying pathogens in clinical samples. Mining through metagenomes can be difficult given the volume of reads, overwhelming human contamination, and lack of well-defined bioinformatics methods. The goal of our study was to assess Centrifuge, a leading tool for the identification and quantitation of microbes, and provide a streamlined bioinformatics workflow real-word data from FN patient blood samples. To ensure the accuracy of the workflow we carefully examined each step using known bacterial mixtures that varied by genetic distance and abundance. We show that Centrifuge reliably identifies microbes present at just 1% relative abundance and requires substantially less computer time and resource than CLARK. Moreover, we found that Centrifuge results changed minimally by quality control and host-screening allowing for further reduction in compute time. Next, we leveraged Centrifuge to identify viruses and bacteria in blood draws for three FN patients, and confirmed suspected pathogens using genome coverage plots. We developed a web-based tool in iMicrobe and detailed protocols to promote re-use.

Polyfunctional Biopreparations-Crude Oil Destructors: The Effect on Plants and the Content of Oil in the Soil

The results of an experiment on cleaning oil-contaminated soil and accelerating the restoration of its fertility with the aid of combined biopreparations containing bacteria that degrade oil and microorganisms that can stimulate the growth and development of plants. It is shown that the introduction of bacterial mixtures reduced the oil content by 3.1–3.6 times and increased by 2-3 orders the number of basic physiological groups of soil microorganisms participating in its transformation, and also accelerated the germination of seeds (for 2 days) and the beginning (for 6–7 days) of all stages of oat development, used as a phytomeliorant. The most effective was a biopreparation consisting of a consortium of microorganisms Acinetobacter calcoaceticus IB DT-5.1/ 1 and Ochrobactrum intermedium IB DT-5.3/2 and strains of Pseudomonas koreensis IB-4 and Paenibacillus ehimensis IB 739, which, among other things, increased the mass of oat shoots in 2.3–2.6 times and their length is 54.0–77.8% compared to plants in the soil untreated with bacteria with oil.