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Poultry industry in Nepal has experienced remarkable growth in the last decade, but farm biosafety and biosecurity measures are often overlooked by farmers due to lack of knowledge or to save cost. As a result, farms often suffer from sporadic and regular outbreaks of many zoonotic diseases such as highly pathogenic avian influenza (HPAI), impacting production and creating public health challenges. Poor farm management practices, including overuse of antibiotics for prophylaxis and therapeutics, can complicate the spread of poultry diseases by creating and enhancing antimicrobial resistance (AMR) that is threating to both, poultry, and human health.We assessed biosafety, biosecurity risks and AMR stewardship in sixteen poultry farms located in four districts (Ramechhap, Nuwakot, Sindhupalchowk, and Kavre) surrounding densely populated Kathmandu valley. Risk assessment and AMR stewardship evaluation questionnaire were administered to formulate biosafety and biosecurity compliance matrix (BBCM). Risk assessment checklist assessed facility operations, personnel and standard operating procedures, water supply, cleaning and maintenance, rodent/pest control and farm record keeping. Oral and cloacal samples from the poultry were collected, pooled, and screened for eight poultry pathogens using Polymerase Chain Reaction (PCR) tests.Based on BBCM, we identified one of the farms in Sindhupalchowk (Farm 4) having the most (BBCM score= 67%) and a farm in Kavre (Farm 3) to having the least (BBCM score= 12%) biosafety and biosecurity compliance. Although most of the farms (61.6%) followed general poultry farming practices, only half had clean and well-maintained farms. Personal safety standard procedure compliance (BBCM score = 42.4%) and rodent control (BBCM score = 3.1%) were the biggest gaps. At least one of either bacterial or viral pathogen was detected in all farms.Mycoplasma gallisepticumwas the most common disease detected in all but one farm, followed byMycoplasma synoviae. Although more than half of the farmers considered AMR a threat, over 26% of them used antibiotics as a preventive measure and 81% did not consider withdrawal period for antibiotics prior to processing of their meat products. Additionally, antibiotics classified as Watch and Restrict by the WHO were frequently used by the farmers to treat bacterial infections in their farms. Lack of awareness and inadequate enforcement of regulations have exacerbated the risk of disease transmission in farms and compromised antimicrobial stewardship.

Antimicrobial resistance (AMR) is an emerging and growing global health challenge that could result in 10.2 million deaths annually by 2050. The unrestricted and haphazard use of antibiotics is contributing to the rapid emergence and spread of AMR, and the problem is exacerbated by release of untreated waste water from high-risk sources like hospitals into rivers. Bacteria often develop resistance through horizontal gene transfer mechanism and gut flora can act as a source for new Antimicrobial Resistance Genes (ARG). Upcoming methods like metagenomics can identify the resistance profile (AMR) of gut microbiome, and detect bacterial infections that otherwise go unnoticed. Our study focused on understanding the presence of AMR mutations and gene transfer dynamics in human, animal and environmental samples collected in one of the temporary settlements of Kathmandu (Nepal) using One Health approach. Current AMR reporting based on clinical cases is limited and does not provide information on specific pathogen and associated AMR genes-our study is an effort to contribute information to fulfill this gap.Twenty-one samples were collected from a temporary settlement in Thapathali (Kathmandu), which included fecal samples from birds (n=3) and humans (n=14), and environmental samples (n=4). Microbiological assessment was carried out based on 16S sequence metagenomic analysis using MiSeq (Illumina, USA). Taxonomic classification on obtained 16S sequences were determined by using Metaphlan 2 and Qiime 2 bioinformatics tools. ShortBRED was used to classify ARG and virulence factors, and WAFFLE was used for horizontal gene transfer event prediction. The network analysis was carried out using Gephi v0.9 and the ResistoXplorer web tool to identify ARG in the collected samples.Prevotella spp. was the dominant gut microbiome in humans. We detected diverse phages and viruses, including Stx-2 converting phages. 72 virulence factors and 53 ARG subtypes were detected, with poultry samples having the highest number of subtypes. The cluster and network analysis showed a strong association between gut microbiome and ARG, which was also supported by Horizontal Gene Transfer (HGT) analysis. One-Health interface showed ARG dynamics and revealed gut microbiomes of humans and animals serving as a reservoir for the circulating ARG.

Although over 180 freshwater fish species have been reported from Nepal, little is known of their ecology and distribution. This information is needed because their diversity may be threatened by developments like hydropower constructions. We conducted Nepal’s first environmental DNA (eDNA) based fish biodiversity assessment in two major river systems- Karnali River (KR), which is still pristine and Trishuli River (TR) with numerous hydropower plants. The eDNA was concentrated by filtering (0.45 μm pore size) two liters of water collected at different sampling points in each study site. A total of 224 eDNA samples (KR=162 and TR= 62) were collected, from which fish species was identified by 12S rRNA metabarcording approach utilizing Illumina sequencing platform. Alpha and beta diversity of species between two sites were compared. Also, in KR site, fish (N=795) were caught, and identified using COI based DNA barcoding- building Nepal’s first fish DNA reference database. Field sampling identified 21 species through morphology and DNA barcoding, where Barilius spp. and Schizothorax spp. were the most abundant. From 244 eDNA samples, 24 Operational Taxonomic Units (OTUs) were identified in TR and 46 in KR with 19 being common to both sites, 27 being unique in KR, and five in TR only. Most fishes were of Cypriniformes and Siluriformes orders, with Barilius spp. and Schizothorax spp. being the most abundant. Long distance migratory fish (Tor spp, Neolissochilus hexagonolepis) and non-native fish (Cyprinus carpio, Hypophthalmichthys molitrix, Gymnocorymbuster netzi, Ctenopharyngo donidella, Clarias gariepinus) were identified in eDNA samples as well. Alpha diversity in TR was significantly lower than in KR. High beta diversity between the two sites indicated low similarity in fish diversity between the TR and KR. This study demonstrated the utility of eDNA as a non-invasive technique for biodiversity assessment which is particularly useful in areas like Nepal with scarce data on fish species distribution.

BackgroundCommercial hatcheries play an important role in the overall poultry value chain-providing small to large poultry farmers with day old chicks. Any outbreak in such hatcheries can spread diseases to other farms. Regular screening of major avian pathogens, along with strict bio-security measures, can prevent spread of diseases in hatcheries. Newcastle Disease Virus (NDV), Infectious Bronchitis Virus (IBV), Mycoplasma gallisepticum (MG), Mycoplasma synoviae (MS), Infectious Bursal Disease Virus (IBDV) and Influenza A Virus (IAV) are among the most prevalent poultry diseases which can be detected in egg albumin.MethodWe retrospectively (August 2020-August 2021, except October 2020) analyzed diagnostic results for six selected avian pathogens (NDV, IBV, MS, MG, IBDV and IAV) on eggs (n=4343) received from eleven major commercial poultry hatcheries located in the five adjoining districts of Kathmandu, Nepal. Albumin from 10% randomly selected eggs from each hatchery were tested for the six avian pathogens using multiplex PCR.ResultMajority (7/11, 64%) of the poultry hatcheries had at least one of the six pathogens present. We detected at least one avian pathogen in nine out of eleven months (82%) of screening. Except for IBDV, we found one or more of the other major avian pathogens-Influenza A (IAV) (n=4 times) and Mycoplasma gallisepticum (MG) (n=4 times) were detected the most, followed by Newcastle Virus (NDV) (n=3 times). Infectious bronchitis virus (IBV) were detected twice, and Mycoplasma synoviae (MS) was detected once.ConclusionIn a resource strapped country like Nepal, poultry disease outbreak investigation in particular and surveillance in general are challenging. Meanwhile, poultry production is highly impacted by disease outbreaks often triggered by poor bio-security and lack of pathogen screening practices. Our molecular screening tests have picked up major poultry pathogens present throughout the year in eggs collected from hatcheries. Influenza A was detected at 4 different incidences throughout the year, which is of concern to both human and animal health. Quick systematic screening of eggs at key distribution points (hatcheries) for major avian pathogens is an effective surveillance tool for early disease detection and containment of outbreaks.

Background:The current COVID-19 pandemic, previous several viral pandemics and seasonal influenza raise important questions about synergic interactions between the SARS-CoV-2 virus and bacterial co-infection. It is a needs time to determine if co-infection with antibiotic-resistant bacteria affects disease severity. Indeed, some of the pathogens detected in COVID-19 patients could be antibiotic-resistant, which could reduce the efficacy of treatments administered to patients. Unfortunately, there is no such study from Nepal which describes the specific co-infecting pathogens and no studies thus far have analyzed rates of co-infection by antibiotic-resistant bacteria. Thus, it is impossible to determine from the available data whether certain bacterial species or antibiotic-resistant strains correlate with outcome severity or mortality. However, the presence of antibiotic-resistant bacteria could potentially explain the high rates of bacterial co-infections in critically ill patients despite extensive antibiotic treatments in this study.Therefore, in the present study, we collected respiratory, blood, and urine samples from lab-confirmed cases of COVID-19 hospitalized patients. The study aims to identify co-infection and secondary bacterial infection to obtain the etiology and antimicrobial resistance for more accurate antimicrobial use.Objective:General Objectives:To detect the presence of co-infection and secondary bacterial infection in covid-19 hospitalized patients.Specific Objectives:1. To determine the antibiotic susceptibility pattern of clinical isolates from the covid-19 positive hospitalized patients.2. To determine the type of antimicrobial resistance in the clinical isolates from the covid-19 positive hospitalized patients.Materials and Methods:We performed a prospective descriptive study, in which we had received three different clinical specimens such as blood, urine, and respiratory samples (sputum, ETT aspirate, BAL, etc…) submitted for bacterial culture and sensitivity tests to the department of microbiology at the National Public Health Laboratory (NPHL) during the study period from January to July 2021. The clinical samples were received from 200 symptomatic, lab-confirmed COVID-19 hospitalized patients admitted at Sukraja Tropical and Infectious Diseases Hospital, Teku; Kathmandu, Nepal. The specimens were processed in two different phases. The first samples were collected within 48 hours of hospital admission which propose the bacterial co-infection. The second samples were taken after 48 hours of admission.Results:The findings were consistent with the national data as the majority of the infected patients were male (n=123) and most of the infected (n=145) belonged to the working-age group (21 to 70 years) (5). The mean age of infected patients was 53.24 years. 177 of the total patients in this study (88.5%) were admitted with either severe or moderate Covid symptoms. Additionally, this translated into 173 of 200 patients (86.5%) spending a week or more at the hospital with 18.5% being admitted for more than a month. The highlights the resistance to various antibiotics detected from either sputum, blood, or urine samples from patients with different co-morbidities. The ten most AMR-resistant antibiotics cultured from sputum were as follows - 328 were resistant to Ciprofloxacin, 304 each for Gentamycin, Levofloxacin, and Amikacin, 288 for Cotrimoxazole, 280 each for Cefotaxime and Piperacillin Tazobactum, 264 for Azithromycin, 256 for Ceftazidime, and 248 for Ampicillin.Conclusion:Covid-19 has had a devastating impact on population throughout the world and in a third world country like Nepal, this study provides a unique insight into multiple factors that exacerbate health conditions. Despite having limited data from one hospital, the findings of the study mimicked national data patterns regarding the demographics most affected (working population). It also highlighted the statistical significance among the impact of age and other respiratory co-illnesses have on further aggravating issues with Covid-19 infections. More importantly, the study also discovered the presence of MDR or even extremely drug-resistant (XDR) bacteria among patients admitted with a bacterial co-infection and secondary bacterial infection. It recommends Antimicrobial stewardship, strict infection control and prevention should be implicated in all health sections.

Spot blotch caused by Bipolaris sorokiniana has spread to more than 9 million ha of wheat in the warm, humid areas of the Eastern Gangetic Plains (EGP) of South Asia and is a disease of major concern in other similar wheat growing regions worldwide. Differential lignin content in resistant and susceptible genotypes and its association with free radicals such as hydrogen peroxide (H2O2), superoxide (O2-) and hydroxyl radical (OH-) were studied after inoculation under field conditions for two consecutive years. H2O2 significantly influenced lignin content in flag leaves, whereas there was a negative correlation among lignin and H2O2 to the Area Under Disease Progress Curve (AUDPC). The production of H2O2 was higher in the resistant genotypes than susceptible ones. The O2- and OH- positively correlated with AUDPC but negatively with lignin content. This study illustrates that H2O2 has a vital role in prompting lignification and thereby resistance to spot blotch in wheat. We used cluster analysis to separate the resistant and susceptible genotypes by phenotypic and biochemical traits. H2O2 associated lignin production significantly reduced the number of appressoria and penetration pegs. We visualized the effect of lignin in disease resistance using differential histochemical staining of tissue from resistant and susceptible genotypes, which shows the variable accumulation of hydrogen peroxide and lignin around penetration sites.

Understanding disease burden and transmission dynamics in resource-limited, developing countries like Nepal is often challenging due to a lack of adequate surveillance systems. These issues are exacerbated by limited access to diagnostic and research facilities throughout the country. Nepal has one of the highest COVID-19 case rates (915 cases per 100,000 people) in South Asia, with densely-populated Kathmandu experiencing the highest number of cases. Swiftly identifying case clusters and introducing effective intervention programs is crucial to mounting an effective containment strategy. The rapid identification of circulating SARS-CoV-2 variants can also provide important information on viral evolution and epidemiology. Genomic-based environmental surveillance can help in the early detection of outbreaks before clinical cases are recognized, and identify viral micro-diversity that can be used for designing real-time risk-based interventions. This research aimed to develop a genomic-based environmental surveillance system by detecting and characterizing SARS-CoV-2 in sewage samples of Kathmandu using portable next-generation DNA sequencing devices. Out of 20 selected sites in the Kathmandu Valley, sewage samples from 16 (80%) sites had detectable SARS-CoV-2. A heat-map was created to visualize transmission activity in the community based on viral load intensity and corresponding geospatial data. Further, 41 mutations were observed in the SARS-CoV-2 genome. Some detected mutations (n=9, 2%) were novel and yet to be reported in the global database, with one indicating a frameshift deletion in the spike gene. We also observed more transition than transversion on detected mutations, indicating rapid viral evolution in the host. Our study has demonstrated the feasibility of rapidly obtaining vital information on community transmission and disease dynamics of SARS-CoV-2 using genomic-based environmental surveillance.