Genomic diversity of the locally developed Latvian Darkheaded sheep breed.

The Latvian Darkheaded is the only locally developed sheep breed. The breed was formed at the beginning of the 20th century by crossing local coarse-wooled sheep with the British Shropshire and Oxfordshire breeds. The breed was later improved by adding Ile-de-France, Texel, German blackheads, and Finnsheep to achieve higher prolificacy and better meat quality. Previous studies have reported the Latvian Darkheaded sheep to be closely related to Estonian and Lithuanian Blackface breeds, according to microsatellite data. To expand our knowledge of the genetic resources of the Latvian Darkheaded breed, we conducted a whole-genome resequencing analysis on 40 native sheep. The investigation showed that local sheep harbor genetic diversity levels similar to those observed among other improved breeds of European origin, including Charollais and Suffolk. Genome-wide nucleotide diversity (π) in Latvian Darkheaded sheep was 3.91 × 10-3, whereas the average observed heterozygosity among the 40 animals was 0.267 and 0.438 within the subsample of unrelated individuals. The Ne has rapidly decreased to 200 ten generations ago with a recent drop to Ne 73 four generations ago. However, inbreeding levels based on runs of homozygosity were, on average, low, with FROH ranging between 0.016 and 0.059. The analysis of the genomic composition of the breed confirmed shared ancestry with sheep of British origin, reflecting the history of the breed. Nevertheless, Latvian Darkheaded sheep were genetically separable. The contemporary Latvian Darkheaded sheep population is genetically diverse with a low inbreeding rate. However, further development of breed management programs is necessary to prevent an increase in inbreeding, loss of genetic diversity, and depletion of breed-specific genetic resources, ensuring the preservation of the native Latvian Darkheaded sheep.

Genomic Characterization and Initial Insight into Mastitis-Associated SNP Profiles of Local Latvian Bos taurus Breeds.

Latvia has two local Bos taurus breeds-Latvian Brown (LBG) and Latvian Blue (LZG)-characterized by a good adaptation to the local climate, longevity, and high fat and protein contents in milk. Since these are desired traits in the dairy industry, this study investigated the genetic background of the LBG and LZG breeds and identified the genetic factors associated with mastitis. Blood and semen samples were acquired, and whole genome sequencing was then performed to acquire a genomic sequence with at least 35× or 10× coverage. The heterozygosity, nucleotide diversity, and LD analysis indicated that LBG and LZG cows have similar levels of genetic diversity compared to those of other breeds. An analysis of the population structure revealed that each breed clustered together, but the overall differentiation between the breeds was small. The highest genetic variance was observed in the LZG breed compared with the LBG breed. Our results show that SNP rs721295390 is associated with mastitis in the LBG breed, and SNPs rs383806754, chr29:43998719CG>C, and rs462030680 are associated with mastitis in the LZG breed. This study shows that local Latvian LBG and LZG breeds have a pronounced genetic differentiation, with each one suggesting its own mastitis-associated SNP profile.

Abundance and prevalence of ESBL coding genes in patients undergoing first line eradication therapy for Helicobacter pylori.

The spread of extended-spectrum beta-lactamases (ESBLs) in nosocomial and community-acquired enterobacteria is an important challenge for clinicians due to the limited therapeutic options for infections that are caused by these organisms. Here, we developed a panel of ESBL coding genes, evaluated the abundance and prevalence of ESBL encoding genes in patients undergoing H. pylori eradication therapy, and summarized the effects of eradication therapy on functional profiles of the gut microbiome. To assess the repertoire of known beta lactamase (BL) genes, they were divided into clusters according to their evolutionary relation. Primers were designed for amplification of cluster marker regions, and the efficiency of this amplification panel was assessed in 120 fecal samples acquired from 60 patients undergoing H. pylori eradication therapy. In addition, fecal samples from an additional 30 patients were used to validate the detection efficiency of the developed ESBL panel. The presence for majority of targeted clusters was confirmed by NGS of amplification products. Metagenomic sequencing revealed that the abundance of ESBL genes within the pool of microorganisms was very low. The global relative abundances of the ESBL-coding gene clusters did not differ significantly among treatment states. However, at the level of each cluster, classical ESBL producers such as Klebsiella sp. for blaOXY (p = 0.0076), Acinetobacter sp. for blaADC (p = 0.02297) and others, differed significantly with a tendency to decrease compared to the pre- and post-eradication states. Only 13 clusters were common across all three datasets, suggesting a patient-specific distribution profile of ESBL-coding genes. The number of AMR genes detected in the post-eradication state was higher than that in the pre-eradication state, which could be attributed, at least in part, to the therapy. This study demonstrated that the ESBL screening panel was effective in targeting ESBL-coding gene clusters from bacterial DNA and that minor differences exist in the abundance and prevalence of ESBL-coding gene levels before and after eradication therapy.

Wastewater-based prediction of COVID-19 cases using a random forest algorithm with strain prevalence data: A case study of five municipalities in Latvia.

Wastewater-based epidemiology (WBE) is a rapid and cost-effective method that can detect SARS-CoV-2 genomic components in wastewater and can provide an early warning for possible COVID-19 outbreaks up to one or two weeks in advance. However, the quantitative relationship between the intensity of the epidemic and the possible progression of the pandemic is still unclear, necessitating further research. This study investigates the use of WBE to rapidly monitor the SARS-CoV-2 virus from five municipal wastewater treatment plants in Latvia and forecast cumulative COVID-19 cases two weeks in advance. For this purpose, a real-time quantitative PCR approach was used to monitor the SARS-CoV-2 nucleocapsid 1 (N1), nucleocapsid 2 (N2), and E genes in municipal wastewater. The RNA signals in the wastewater were compared to the reported COVID-19 cases, and the strain prevalence data of the SARS-CoV-2 virus were identified by targeted sequencing of receptor binding domain (RBD) and furin cleavage site (FCS) regions employing next-generation sequencing technology. The model methodology for a linear model and a random forest was designed and carried out to ascertain the correlation between the cumulative cases, strain prevalence data, and RNA concentration in the wastewater to predict the COVID-19 outbreak and its scale. Additionally, the factors that impact the model prediction accuracy for COVID-19 were investigated and compared between linear and random forest models. The results of cross-validated model metrics showed that the random forest model is more effective in predicting the cumulative COVID-19 cases two weeks in advance when strain prevalence data are included. The results from this research help inform WBE and public health recommendations by providing valuable insights into the impact of environmental exposures on health outcomes.

Oral Microbiome Traits of Type 1 Diabetes and Phenylketonuria Patients in Latvia.

Some metabolic disorder treatments require patients to follow a specific diet or to consume supplements that, over time, can lead to oral microbiome alterations. Well-known disorders requiring such treatment are phenylketonuria (PKU), an inborn error of amino acid metabolism, and type 1 diabetes (T1D), a metabolic disorder that requires a specific diet regimen. Therefore, the aim of this study was to investigate the oral health and microbiome characteristics that might contribute to caries activity and periodontal disease risk in PKU and T1D patients. In this cross-sectional study, 45 PKU patients, 24 T1D patients, and 61 healthy individuals between the ages of 12 and 53 years were examined. Their anamnestic data and dental status were assessed by one dentist. Microbial communities were detected from saliva-isolated DNA using 16S rRNA gene V3-V4 sequencing on Illumina MiSeq sequencing platform. Results revealed that the PKU patient group displayed the highest number of extracted teeth (on average 1.34), carious teeth (on average 4.95), and carious activity (44.44% of individuals) compared to the T1D and CTRL groups. The lowest numbers of filled teeth (on average 5.33) and extracted teeth (on average 0.63) per individual were observed in T1D patients. Gingivitis appeared more often in the T1D group; however, possible risk of periodontal disease was seen in both the T1D and PKU patient groups. The highest number of differentially abundant genera was detected in the PKU group (n = 20), with enrichment of Actinomyces (padj = 4.17 × 10-22), Capnocytophaga (padj = 8.53 × 10-8), and Porphyromonas (padj = 1.18 × 10-5) compared to the CTRL group. In conclusion, the dental and periodontal health of PKU patients was found to be significantly inferior compared to T1D patients and healthy controls. T1D patients showed early signs of periodontal disease. Several genera that correlate with periodontal disease development were found in both groups, thus suggesting that T1D and PKU patients should seek early and regular dental advice and be educated about proper oral hygiene practices.