Bacterial colony size growth estimation by deep learning.

The bacterial growth rate is important for pathogenicity and food safety. Therefore, the study of bacterial growth rate over time can provide important data from a medical and veterinary point of view. We trained convolutional neural networks (CNNs) on manually annotated solid medium cultures to detect bacterial colonies as accurately as possible. Predictions of bacterial colony size and growth rate were estimated from image sequences of independent Staphylococcus aureus cultures using trained CNNs. A simple linear model for control cultures with less than 150 colonies estimated that the mean growth rate was 60.3 [Formula: see text] for the first 24 h. Analyzing with a mixed effect model that also takes into account the effect of culture, smaller values of change in colony size were obtained (control: 51.0 [Formula: see text], rifampicin pretreated: 36.5[Formula: see text]). An increase in the number of neighboring colonies clearly reduces the colony growth rate in the control group but less typically in the rifampicin-pretreated group. Based on our results, CNN-based bacterial colony detection and the subsequent analysis of bacterial colony growth dynamics might become an accurate and efficient tool for bacteriological work and research.

Natural diversity of the honey bee (Apis mellifera) gut bacteriome in various climatic and seasonal states.

As pollinators and producers of numerous human-consumed products, honey bees have great ecological, economic and health importance. The composition of their bacteriota, for which the available knowledge is limited, is essential for their body's functioning. Based on our survey, we performed a metagenomic analysis of samples collected by repeated sampling. We used geolocations that represent the climatic types of the study area over two nutritionally extreme periods (March and May) of the collection season. Regarding bacteriome composition, a significant difference was found between the samples from March and May. The samples' bacteriome from March showed a significant composition difference between cooler and warmer regions. However, there were no significant bacteriome composition differences among the climatic classes of samples taken in May. Based on our results, one may conclude that the composition of healthy core bacteriomes in honey bees varies depending on the climatic and seasonal conditions. This is likely due to climatic factors and vegetation states determining the availability and nutrient content of flowering plants. The results of our study prove that in order to gain a thorough understanding of a microbiome's natural diversity, we need to obtain the necessary information from extreme ranges within the host's healthy state.

Genetic analyses of the endocannabinoid pathway in association with affective phenotypic variants.

BACKGORUND: Increasing experimental data confirm the crucial role of the endocannabinoid (eCB) system in the regulation of stress response and emotional processes. Despite of the fact, that genetically determined vulnerability for stress is a widely accepted concept in the pathomechanism of affective disorders, replicable human genetic results with interaction analyses of early life trauma and eCB genes are rare. The aim of this study is to test the associations between genetic variants of the eCB pathway, childhood trauma and affective phenotypes. METHODS: We selected 18,897 SNPs in the eCB pathway of a GWAS dataset in two general population cohorts (BP sample N = 837; MN sample N = 988). Association analyses were performed on the anxious and depressive subscales of the Brief Symptom Inventory (BSI-ANX and BSI-DEP, respectively). Childhood trauma was assessed by the Childhood Adversity Questionnaire (CAQ). Association analyses were performed in the R 2.0. statistical program using the SNPassoc package. REULTS: Genetic effect was more robust in the BP sample than in the MN sample. The most comprehensive results showed that SNPs in the CACNA1C gene associated with depressive phenotype in interaction with CAQ in both BP (p = 1.2 × 10-4) and MN samples (p = 1.6 × 10-4). Direct association analyses (without interaction) provided significant associations between SNPs in different genesets of the two study populations. SNPs in KCNJ3 and GNB5 genes on the BSI-DEP (p = 6.1 × 10-5; p = 7.1 × 10-4) and GNG12 gene on the BSI-ANX (p = 7.4 × 10-6) in the BP sample, while GABAergic, ADCY1 and HTR2A gene variants can be outlined from results of MN sample with less strong p-values. CONCLUSION: Our results confirmed the prominent role of CACNA1C gene in the pathogenic effect of early life stress in the development of affective vulnerability in two different study populations using GxE interaction analysis. CACNA1C gene, as it encodes for L-type voltage-gated calcium channel, contributes to neuronal excitability, plasticity and neurogenesis being a crucial effector of both eCB signaling and the BDNF-CREB pathway as well. Our findings suggest that childhood trauma related depression may have more robust genetically determined basis than without early life stress.

Antimicrobial resistance genes in raw milk for human consumption.

The increasing prevalence of antimicrobial resistance (AMR) is a significant threat to global health. More and more multi-drug-resistant bacterial strains cause life-threatening infections and the death of thousands of people each year. Beyond disease control animals are often given antibiotics for growth promotion or increased feed efficiency, which further increase the chance of the development of multi-resistant strains. After the consumption of unprocessed animal products, these strains may meet the human bacteriota. Among the foodborne and the human populations, antimicrobial resistance genes (ARGs) may be shared by horizontal gene transfer. This study aims to test the presence of antimicrobial resistance genes in milk metagenome, investigate their genetic position and their linkage to mobile genetic elements. We have analyzed raw milk samples from public markets sold for human consumption. The milk samples contained genetic material from various bacterial species and the in-depth analysis uncovered the presence of several antimicrobial resistance genes. The samples contained complete ARGs influencing the effectiveness of acridine dye, cephalosporin, cephamycin, fluoroquinolone, penam, peptide antibiotics and tetracycline. One of the ARGs, PC1 beta-lactamase may also be a mobile element that facilitates the transfer of resistance genes to other bacteria, e.g. to the ones living in the human gut.