Apis mellifera filamentous virus from a honey bee gut microbiome survey in Hungary.

In Hungary, as part of a nationwide, climatically balanced survey for a next-generation sequencing-based study of the honey bee (Apis mellifera) gut microbiome, repeated sampling was carried out during the honey production season (March and May 2019). Among other findings, the presence of Apis mellifera filamentous virus (AmFV) was detected in all samples, some at very high levels. AmFV-derived reads were more abundant in the March samples than in the May samples. In March, a higher abundance of AmFV-originated reads was identified in samples collected from warmer areas compared to those collected from cooler areas. A lower proportion of AmFV-derived reads were identified in samples collected in March from the wetter areas than those collected from the drier areas. AmFV-read abundance in samples collected in May showed no significant differences between groups based on either environmental temperature or precipitation. The AmFV abundance correlated negatively with Bartonella apihabitans, Bartonella choladocola, and positively with Frischella perrara, Gilliamella apicola, Gilliamella sp. ESL0443, Lactobacillus apis, Lactobacillus kullabergensis, Lactobacillus sp. IBH004. De novo metagenome assembly of four samples resulted in almost the complete AmFV genome. According to phylogenetic analysis based on DNA polymerase, the Hungarian strains are closest to the strain CH-05 isolated in Switzerland.

Comparative examination of a rapid immunocytochemical test for the detection of highly pathogenic avian influenza virus in domestic birds in field outbreaks.

RESEARCH HIGHLIGHTS: Avian influenza virus (AIV) antigen detection was examined in field outbreaks.Bird brain smears were tested using immunocytochemistry (IC).IC results strongly correlated with real-time RT-PCR results.The IC method was rapid, specific, sensitive, and cost-effective in AIV field outbreaks.

Ixodes ricinus tick bacteriome alterations based on a climatically representative survey in Hungary.

IMPORTANCE: Climate-sensitive disease vectors, such as ticks, respond to the environment with changes in their microbiome. These changes can affect the emergence or re-emergence of various vector-borne pathogens, such as the causative agent of Lyme borreliosis (LB) or tick-borne encephalitis. This aspect is particularly emphasized in light of climate change. The climatically representative assessment of microbiome differences in various developmental stages of the most common Central European tick species, Ixodes ricinus, deepens our understanding of the potential climatic factors behind microbial relative abundance and interaction changes. This knowledge can support the development of novel disease vector control strategies.

First Molecular Identification of Calicophoron daubneyi (Dinnik, 1962) and Paramphistomum leydeni (Nasmark, 1937) in Wild Ruminants from Romania.

Rumen flukes are geographically widespread trematodes affecting wild and domestic ruminants. The juvenile forms, which are found in the small intestine, are more pathogenic compared to the adults. Severe diarrhoea and weight loss are the major clinical signs, and the disease might be fatal in severely infested individuals. In the last decade, paramphistomosis has been described as an emerging parasitic disease in Europe. This study aimed to identify the rumen fluke species in wild ruminants from western Romania. Fifty-two pre-stomachs obtained from roe deer (Capreolus capreolus) that were hunted on 14 hunting grounds from Timiș and Arad counties were examined for the presence of paramphistomes. Three (9.09%) out of 33 samples were positive in Timiș County, and one (5.26%) out of 19 samples was positive in Arad County. Subsequent PCR testing revealed that three samples were positive for Calicophoron daubneyi and one for Paramphistomum leydeni. The presence of C. daubneyi and P. leydeni in roe deer has not been previously reported in Romania. Two Paramphistomum species-C. daubneyi and P. leydeni-were revealed as the main species of rumen flukes in roe deer from forests in Romania.

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.

A biallelic multiple nucleotide length polymorphism explains functional causality at 5p15.33 prostate cancer risk locus.

To date, single-nucleotide polymorphisms (SNPs) have been the most intensively investigated class of polymorphisms in genome wide associations studies (GWAS), however, other classes such as insertion-deletion or multiple nucleotide length polymorphism (MNLPs) may also confer disease risk. Multiple reports have shown that the 5p15.33 prostate cancer risk region is a particularly strong expression quantitative trait locus (eQTL) for Iroquois Homeobox 4 (IRX4) transcripts. Here, we demonstrate using epigenome and genome editing that a biallelic (21 and 47 base pairs (bp)) MNLP is the causal variant regulating IRX4 transcript levels. In LNCaP prostate cancer cells (homozygous for the 21 bp short allele), a single copy knock-in of the 47 bp long allele potently alters the chromatin state, enabling de novo functional binding of the androgen receptor (AR) associated with increased chromatin accessibility, Histone 3 lysine 27 acetylation (H3K27ac), and ~3-fold upregulation of IRX4 expression. We further show that an MNLP is amongst the strongest candidate susceptibility variants at two additional prostate cancer risk loci. We estimated that at least 5% of prostate cancer risk loci could be explained by functional non-SNP causal variants, which may have broader implications for other cancers GWAS. More generally, our results underscore the importance of investigating other classes of inherited variation as causal mediators of human traits.

Development of a versatile LCM-Seq method for spatial transcriptomics of fluorescently tagged cholinergic neuron populations.

Single-cell transcriptomics are powerful tools to define neuronal cell types based on co-expressed gene clusters. Limited RNA input in these technologies necessarily compromises transcriptome coverage and accuracy of differential expression analysis. We propose that bulk RNA-Seq of neuronal pools defined by spatial position offers an alternative strategy to overcome these technical limitations. We report a laser-capture microdissection (LCM)-Seq method which allows deep transcriptome profiling of fluorescently tagged neuron populations isolated with LCM from histological sections of transgenic mice. Mild formaldehyde fixation of ZsGreen marker protein, LCM sampling of ∼300 pooled neurons, followed by RNA isolation, library preparation and RNA-Seq with methods optimized for nanogram amounts of moderately degraded RNA enabled us to detect ∼15,000 different transcripts in fluorescently labeled cholinergic neuron populations. The LCM-Seq approach showed excellent accuracy in quantitative studies, allowing us to detect 2891 transcripts expressed differentially between the spatially defined and clinically relevant cholinergic neuron populations of the dorsal caudate-putamen and medial septum. In summary, the LCM-Seq method we report in this study is a versatile, sensitive, and accurate bulk sequencing approach to study the transcriptome profile and differential gene expression of fluorescently tagged neuronal populations isolated from transgenic mice with high spatial precision.

Annotated dataset for deep-learning-based bacterial colony detection.

Quantifying bacteria per unit mass or volume is a common task in various fields of microbiology (e.g., infectiology and food hygiene). Most bacteria can be grown on culture media. The unicellular bacteria reproduce by dividing into two cells, which increases the number of bacteria in the population. Methodologically, this can be followed by culture procedures, which mostly involve determining the number of bacterial colonies on the solid culture media that are visible to the naked eye. However, it is a time-consuming and laborious professional activity. Addressing the automation of colony counting by convolutional neural networks in our work, we have cultured 24 bacteria species of veterinary importance with different concentrations on solid media. A total of 56,865 colonies were annotated manually by bounding boxes on the 369 digital images of bacterial cultures. The published dataset will help developments that use artificial intelligence to automate the counting of bacterial colonies.

Antimicrobial resistance gene lack in tick-borne pathogenic bacteria.

Tick-borne infections, including those of bacterial origin, are significant public health issues. Antimicrobial resistance (AMR), which is one of the most pressing health challenges of our time, is driven by specific genetic determinants, primarily by the antimicrobial resistance genes (ARGs) of bacteria. In our work, we investigated the occurrence of ARGs in the genomes of tick-borne bacterial species that can cause human infections. For this purpose, we processed short/long reads of 1550 bacterial isolates of the genera Anaplasma (n = 20), Bartonella (n = 131), Borrelia (n = 311), Coxiella (n = 73), Ehrlichia (n = 13), Francisella (n = 959) and Rickettsia (n = 43) generated by second/third generation sequencing that have been freely accessible at the NCBI SRA repository. From Francisella tularensis, 98.9% of the samples contained the FTU-1 beta-lactamase gene. However, it is part of the F. tularensis representative genome as well. Furthermore, 16.3% of them contained additional ARGs. Only 2.2% of isolates from other genera (Bartonella: 2, Coxiella: 8, Ehrlichia: 1, Rickettsia: 2) contained any ARG. We found that the odds of ARG occurrence in Coxiella samples were significantly higher in isolates related to farm animals than from other sources. Our results describe a surprising lack of ARGs in these bacteria and suggest that Coxiella species in farm animal settings could play a role in the spread of AMR.

A survey on antimicrobial resistance genes of frequently used probiotic bacteria, 1901 to 2022.

BackgroundAntimicrobial resistance (AMR) is caused by AMR determinants, mainly genes (ARGs) in the bacterial genome. Bacteriophages, integrative mobile genetic elements (iMGEs) or plasmids can allow ARGs to be exchanged among bacteria by horizontal gene transfer (HGT). Bacteria, including bacteria with ARGs, can be found in food. Thus, it is conceivable that in the gastrointestinal tract, bacteria from the gut flora could take up ARGs from food.AimThe study objective was to gain insight into the ARG set carried by commonly used probiotic bacteria that may enter the human body with non-fermented foods, fermented foods, or probiotic dietary supplements (FFPs) and to assess ARG mobility.MethodsNext generation sequencing whole genome data from 579 isolates of 12 commonly employed probiotic bacterial species were collected from a public repository. Using bioinformatical tools, ARGs were analysed and linkage with mobile genetic elements assessed.ResultsResistance genes were found in eight bacterial species. The ratios of ARG positive/negative samples per species were: Bifidobacterium animalis (65/0), Lactiplantibacillus plantarum (18/194), Lactobacillus delbrueckii (1/40), Lactobacillus helveticus (2/64), Lactococcus lactis (74/5), Leucoconstoc mesenteroides (4/8), Levilactobacillus brevis (1/46), Streptococcus thermophilus (4/19). In 66% (112/169) of the ARG-positive samples, at least one ARG could be linked to plasmids or iMGEs. No bacteriophage-linked ARGs were found.ConclusionThe finding of potentially mobile ARGs in probiotic strains for human consumption raises awareness of a possibility of ARG HGT in the gastrointestinal tract. In addition to existing recommendations, screening FFP bacterial strains for ARG content and mobility characteristics might be considered.

Impact Evaluation of Score Classes and Annotation Regions in Deep Learning-Based Dairy Cow Body Condition Prediction.

Body condition scoring is a simple method to estimate the energy supply of dairy cattle. Our study aims to investigate the accuracy with which supervised machine learning, specifically a deep convolutional neural network (CNN), can be used to retrieve body condition score (BCS) classes estimated by an expert. We recorded images of animals' rumps in three large-scale farms using a simple action camera. The images were annotated with classes and three different-sized bounding boxes by an expert. A CNN pretrained model was fine-tuned on 12 and 3 BCS classes. Training in 12 classes with a 0 error range, the Cohen's kappa value yielded minimal agreement between the model predictions and ground truth. Allowing an error range of 0.25, we obtained minimum or weak agreement. With an error range of 0.5, we had strong or almost perfect agreement. The kappa values for the approach trained on three classes show that we can classify all animals into BCS categories with at least moderate agreement. Furthermore, CNNs trained on 3 BCS classes showed a remarkably higher proportion of strong agreement than those trained in 12 classes. The prediction precision when training with various annotation region sizes showed no meaningful differences. The weights of our trained CNNs are freely available, supporting similar works.

First detection of Ixodiphagus hookeri (Hymenoptera: Encyrtidae) in Ixodes ricinus ticks (Acari: Ixodidae) from multiple locations in Hungary.

The parasitoid wasp, Ixodiphagus hookeri (Hymenoptera: Encyrtidae), is the natural enemy of a wide range of hard and soft tick species. While these encyrtid wasps are supposed to be distributed worldwide, only a few studies report on their actual distribution around the globe. Within a shotgun sequencing-based metagenome analysis, the occurrence of I. hookeri was screened at multiple Ixodes ricinus (Acari: Ixodidae) tick sampling points in Hungary to contribute to the assessment of the distribution patterns of the parasitoid wasps in Central Europe. To our knowledge, the first report of the species in Hungary and the description of the southernmost I. hookeri associated geoposition in Central Europe took place within our study. I. hookeri infested I. ricinus nymphs were detected at five sampling points in Hungary. The results show that the exact distribution range of I. hookeri is still barely studied. At the same time, unprecedented public health issues being brought about by climate change might require steps toward the exploitation of the tick biocontrol potential and as an ecological bioindicator role of the parasitoid wasp in the future.

Canine Saliva as a Possible Source of Antimicrobial Resistance Genes.

While the One Health issues of intensive animal farming are commonly discussed, keeping companion animals is less associated with the interspecies headway of antimicrobial resistance. With the constant advance in veterinary standards, antibiotics are regularly applied in companion animal medicine. Due to the close coexistence of dogs and humans, dog bites and other casual encounters with dog saliva (e.g., licking the owner) are common. According to our metagenome study, based on 26 new generation sequencing canine saliva datasets from 2020 and 2021 reposited in NCBI SRA by The 10,000 Dog Genome Consortium and the Broad Institute within Darwin's Ark project, canine saliva is rich in bacteria with predictably transferable antimicrobial resistance genes (ARGs). In the genome of potentially pathogenic Bacteroides, Capnocytophaga, Corynebacterium, Fusobacterium, Pasteurella, Porphyromonas, Staphylococcus and Streptococcus species, which are some of the most relevant bacteria in dog bite infections, ARGs against aminoglycosides, carbapenems, cephalosporins, glycylcyclines, lincosamides, macrolides, oxazolidinone, penams, phenicols, pleuromutilins, streptogramins, sulfonamides and tetracyclines could be identified. Several ARGs, including ones against amoxicillin-clavulanate, the most commonly applied antimicrobial agent for dog bites, were predicted to be potentially transferable based on their association with mobile genetic elements (e.g., plasmids, prophages and integrated mobile genetic elements). According to our findings, canine saliva may be a source of transfer for ARG-rich bacteria that can either colonize the human body or transport ARGs to the host bacteriota, and thus can be considered as a risk in the spread of antimicrobial resistance.

Shift in the seasonality of ixodid ticks after a warm winter in an urban habitat with notes on morphotypes of Ixodes ricinus and data in support of cryptic species within Ixodes frontalis.

This study was initiated to assess the seasonality and to investigate the morphology of questing ixodid ticks in an urban habitat in Central Europe, Hungary. A neglected part of a large cemetery, with sparse tree covering and dense lower vegetation, was sampled monthly from February 2019 to May 2021. All ticks were analyzed morphologically, and selected specimens by amplifying and sequencing two genetic markers. During the study 3818 ticks were collected, including Ixodes ricinus (n = 2772), Ixodes frontalis (n = 350) and Haemaphysalis concinna (n = 696). Ixodes ricinus adults and nymphs showed year-round activity, whereas H. concinna was not active during winter months and early spring. Most I. frontalis nymphs were collected in late winter and early spring, whereas the peak activity of larvae was during late autumn. Interestingly, during the spring, the peak activity of I. ricinus adults and nymphs was later (in May) when preceded by a warm winter in 2020. In contrast, the 2019 and 2021 spring activity peaks occurred in March and April after sharply rising temperatures in February. This shift in the peak activity of I. ricinus coincided with the initiation of questing activity of H. concinna. Three notably different morphotypes and four malformed specimens of I. ricinus were found. However, these were not significantly different in their mitochondrial haplotypes and phylogenetic clustering from typical specimens of this species. On the other hand, I. frontalis was represented by two remarkably different haplogroups, between which in the nymph stage there were no recognizable morphological differences, suggesting the status of these as cryptic species.

Correction: Papp, M.; Solymosi, N. Review and Comparison of Antimicrobial Resistance Gene Databases. Antibiotics 2022, 11, 339.

While preparing our next manuscript, we noticed a few errors in our published paper [...].

The Effect of Feeding with Central European Local Mulberry Genotypes on the Development and Health Status of Silkworms and Quality Parameters of Raw Silk.

Silkworm rearing activities ceased in the 1970's in several European countries. Attempts on the re-establishment of ecological and sustainable sericulture in Slovenia and Hungary are ongoing. The aim of the study was to assess the usability of locally adapted mulberry genotypes for sericulture and to estimate connections between leaf compound and silkworm performance parameters. A controlled feeding experiment of silkworms was performed to test the influence of leaves from selected trees on the growth of larvae, the health and microbiological status of larvae (e.g., gut bacterial microbiome, Bombyx mori nucleopolyhedrovirus infection), weight of cocoons and raw silk parameters. The Slovenian and Hungarian mulberry genotypes had significantly higher total protein contents, and lower total phenolic contents and differed significantly in some individual phenolics compared to the reference sericultural and fruit varieties. Significant differences were found in the contents of the macro- and microelements, namely S, Mn, Fe, and Sr. Based on correlative statistics and multivariate analysis, a combined positive influence of proteins, specific phenolics, and microelements on larval growth and silk thread parameters was predicted. The results of the study indicate that selected local Slovenian and Hungarian mulberry varieties are suitable for high-quality silk cocoon and raw silk production.

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.

Estrogen differentially regulates transcriptional landscapes of preoptic and arcuate kisspeptin neuron populations.

Kisspeptin neurons residing in the rostral periventricular area of the third ventricle (KPRP3V) and the arcuate nucleus (KPARC) mediate positive and negative estrogen feedback, respectively. Here, we aim to compare transcriptional responses of KPRP3V and KPARC neurons to estrogen. Transgenic mice were ovariectomized and supplemented with either 17ß-estradiol (E2) or vehicle. Fluorescently tagged KPRP3V neurons collected by laser-capture microdissection were subjected to RNA-seq. Bioinformatics identified 222 E2-dependent genes. Four genes encoding neuropeptide precursors (Nmb, Kiss1, Nts, Penk) were robustly, and Cartpt was subsignificantly upregulated, suggesting putative contribution of multiple neuropeptides to estrogen feedback mechanisms. Using overrepresentation analysis, the most affected KEGG pathways were neuroactive ligand-receptor interaction and dopaminergic synapse. Next, we re-analyzed our previously obtained KPARC neuron RNA-seq data from the same animals using identical bioinformatic criteria. The identified 1583 E2-induced changes included suppression of many neuropeptide precursors, granins, protein processing enzymes, and other genes related to the secretory pathway. In addition to distinct regulatory responses, KPRP3V and KPARC neurons exhibited sixty-two common changes in genes encoding three hormone receptors (Ghsr, Pgr, Npr2), GAD-65 (Gad2), calmodulin and its regulator (Calm1, Pcp4), among others. Thirty-four oppositely regulated genes (Kiss1, Vgf, Chrna7, Tmem35a) were also identified. The strikingly different transcriptional responses in the two neuron populations prompted us to explore the transcriptional mechanism further. We identified ten E2-dependent transcription factors in KPRP3V and seventy in KPARC neurons. While none of the ten transcription factors interacted with estrogen receptor-α, eight of the seventy did. We propose that an intricate, multi-layered transcriptional mechanism exists in KPARC neurons and a less complex one in KPRP3V neurons. These results shed new light on the complexity of estrogen-dependent regulatory mechanisms acting in the two functionally distinct kisspeptin neuron populations and implicate additional neuropeptides and mechanisms in estrogen feedback.

Transcriptome profiling of kisspeptin neurons from the mouse arcuate nucleus reveals new mechanisms in estrogenic control of fertility.

Kisspeptin neurons in the mediobasal hypothalamus (MBH) are critical targets of ovarian estrogen feedback regulating mammalian fertility. To reveal molecular mechanisms underlying this signaling, we thoroughly characterized the estrogen-regulated transcriptome of kisspeptin cells from ovariectomized transgenic mice substituted with 17ß-estradiol or vehicle. MBH kisspeptin neurons were harvested using laser-capture microdissection, pooled, and subjected to RNA sequencing. Estrogen treatment significantly (p.adj. < 0.05) up-regulated 1,190 and down-regulated 1,139 transcripts, including transcription factors, neuropeptides, ribosomal and mitochondrial proteins, ion channels, transporters, receptors, and regulatory RNAs. Reduced expression of the excitatory serotonin receptor-4 transcript (Htr4) diminished kisspeptin neuron responsiveness to serotonergic stimulation. Many estrogen-regulated transcripts have been implicated in puberty/fertility disorders. Patients (n = 337) with congenital hypogonadotropic hypogonadism (CHH) showed enrichment of rare variants in putative CHH-candidate genes (e.g., LRP1B, CACNA1G, FNDC3A). Comprehensive characterization of the estrogen-dependent kisspeptin neuron transcriptome sheds light on the molecular mechanisms of ovary-brain communication and informs genetic research on human fertility disorders.