Metagenomic characterization reveals virus coinfections associated with Newcastle disease virus among poultry in Kenya.

Newcastle disease (ND) is an endemic viral disease affecting poultry and causing massive economic losses. This cross-sectional purposive study detected coinfections that are associated with the Newcastle disease virus among poultry from selected regions in Kenya. Cloacal (n = 599) and oral-pharyngeal (n = 435) swab samples were collected and pooled into 17 and 15 samples, respectively. A total of 17,034,948 and 7,751,974 paired-end reads with an average of 200 nucleotides were generated from the cloacal and oral-pharyngeal swab samples, respectively. Analysis of the de novo assembled contigs identified 177 and 18 cloacal and oral-pharyngeal contigs, respectively with hits to viral sequences, as determined by BLASTx and BLASTn analyses. Several known and unknown representatives of Coronaviridae, Picobirnaviridae, Reoviridae, Retroviridae, and unclassified Deltavirus were identified in the cloacal swab samples. However, no Newcastle disease virus (family Paramyxoviridae) was detected in the cloacal swabs, although they were detected in the oropharyngeal swabs of chickens sampled in Nairobi, Busia, and Trans Nzoia. Additionally, sequences representative of Paramyxoviridae, Coronaviridae, and Retroviridae were identified in the oral-pharyngeal swab samples. Infectious bronchitis virus and rotavirus were chickens' most prevalent coinfections associated with the Newcastle disease virus. The detection of these coinfections suggests that these viruses are significant threats to the control of Newcastle disease as the Newcastle disease virus vaccines are known to fail because of these coinfections. Therefore, this study provides important information that will help improve disease diagnosis and vaccine development for coinfections associated with the Newcastle disease virus.

Genomic surveillance of Rift Valley fever virus: from sequencing to lineage assignment.

Genetic evolution of Rift Valley fever virus (RVFV) in Africa has been shaped mainly by environmental changes such as abnormal rainfall patterns and climate change that has occurred over the last few decades. These gradual environmental changes are believed to have effected gene migration from macro (geographical) to micro (reassortment) levels. Presently, 15 lineages of RVFV have been identified to be circulating within the Sub-Saharan Africa. International trade in livestock and movement of mosquitoes are thought to be responsible for the outbreaks occurring outside endemic or enzootic regions. Virus spillover events contribute to outbreaks as was demonstrated by the largest epidemic of 1977 in Egypt. Genomic surveillance of the virus evolution is crucial in developing intervention strategies. Therefore, we have developed a computational tool for rapidly classifying and assigning lineages of the RVFV isolates. The computational method is presented both as a command line tool and a web application hosted at https://www.genomedetective.com/app/typingtool/rvfv/ . Validation of the tool has been performed on a large dataset using glycoprotein gene (Gn) and whole genome sequences of the Large (L), Medium (M) and Small (S) segments of the RVFV retrieved from the National Center for Biotechnology Information (NCBI) GenBank database. Using the Gn nucleotide sequences, the RVFV typing tool was able to correctly classify all 234 RVFV sequences at species level with 100% specificity, sensitivity and accuracy. All the sequences in lineages A (n = 10), B (n = 1), C (n = 88), D (n = 1), E (n = 3), F (n = 2), G (n = 2), H (n = 105), I (n = 2), J (n = 1), K (n = 4), L (n = 8), M (n = 1), N (n = 5) and O (n = 1) were also correctly classified at phylogenetic level. Lineage assignment using whole RVFV genome sequences (L, M and S-segments) did not achieve 100% specificity, sensitivity and accuracy for all the sequences analyzed. We further tested our tool using genomic data that we generated by sequencing 5 samples collected following a recent RVF outbreak in Kenya. All the 5 samples were assigned lineage C by both the partial (Gn) and whole genome sequence classifiers. The tool is useful in tracing the origin of outbreaks and supporting surveillance efforts.Availability: https://github.com/ajodeh-juma/rvfvtyping.

Genome Scan for Variable Genes Involved in Environmental Adaptations of Nubian Ibex.

The Nubian ibex (Capra nubiana) is a wild goat species that inhabits the Sahara and Arabian deserts and is adapted to extreme ambient temperatures, intense solar radiation, and scarcity of food and water resources. To investigate desert adaptation, we explored the possible role of copy number variations (CNVs) in the evolution of Capra species with a specific focus on the environment of Capra nubiana. CNVs are structural genomic variations that have been implicated in phenotypic differences between species and could play a role in species adaptation. CNVs were inferred from Capra nubiana sequence data relative to the domestic goat reference genome using read-depth approach. We identified 191 CNVs overlapping with protein-coding genes mainly involved in biological processes such as innate immune response, xenobiotic metabolisms, and energy metabolisms. We found copy number variable genes involved in defense response to viral infections (Cluster of Differentiation 48, UL16 binding protein 3, Natural Killer Group 2D ligand 1-like, and Interferon-induced transmembrane protein 3), possibly suggesting their roles in Nubian ibex adaptations to viral infections. Additionally, we found copy number variable xenobiotic metabolism genes (carboxylesterase 1, Cytochrome P450 2D6, Glutathione S-transferase Mu 4, and UDP Glucuronosyltransferase-2B7), which are probably an adaptation of Nubian ibex to desert diets that are rich in plant secondary metabolites. Collectively, this study's results advance our understanding of CNVs and their possible roles in the adaptation of Nubian ibex to its environment. The copy number variable genes identified in Nubian ibex could be considered as subjects for further functional characterizations.

Complete avian malaria parasite genomes reveal features associated with lineage-specific evolution in birds and mammals.

Avian malaria parasites are prevalent around the world and infect a wide diversity of bird species. Here, we report the sequencing and analysis of high-quality draft genome sequences for two avian malaria species, Plasmodium relictum and Plasmodium gallinaceum We identify 50 genes that are specific to avian malaria, located in an otherwise conserved core of the genome that shares gene synteny with all other sequenced malaria genomes. Phylogenetic analysis suggests that the avian malaria species form an outgroup to the mammalian Plasmodium species, and using amino acid divergence between species, we estimate the avian- and mammalian-infective lineages diverged in the order of 10 million years ago. Consistent with their phylogenetic position, we identify orthologs of genes that had previously appeared to be restricted to the clades of parasites containing Plasmodium falciparum and Plasmodium vivax, the species with the greatest impact on human health. From these orthologs, we explore differential diversifying selection across the genus and show that the avian lineage is remarkable in the extent to which invasion-related genes are evolving. The subtelomeres of the P. relictum and P. gallinaceum genomes contain several novel gene families, including an expanded surf multigene family. We also identify an expansion of reticulocyte binding protein homologs in P. relictum, and within these proteins, we detect distinct regions that are specific to nonhuman primate, humans, rodent, and avian hosts. For the first time in the Plasmodium lineage, we find evidence of transposable elements, including several hundred fragments of LTR-retrotransposons in both species and an apparently complete LTR-retrotransposon in the genome of P. gallinaceum.

Whole metagenome sequencing of cecum microbiomes in Ethiopian indigenous chickens from two different altitudes reveals antibiotic resistance genes.

We analyzed the whole genomes of cecum microbiomes of Ethiopian indigenous chickens from two distinct geographical zones: Afar (AF) district (Dulecha, 730 m above sea level) and Amhara (AM) district (Menz Gera Midir, 3300 m). Through metagenomic analysis we found that microbial populations were mainly dominated by Bacteroidetes and Firmicutes. We identified 2210 common genes in the two groups. LEfSe showed that the distribution of Coprobacter, Geobacter, Cronobacter, Alloprevotella, and Dysgonomonas were more abundant in AF than AM. Analyses using KEGG, eggNOG, and CAZy databases indicated that the pathways of metabolism, genetic information processing, environmental information processing, and cellular process were significantly enriched. Functional abundance was found to be associated with the nutrient absorption and microbial localization of indigenous chickens. We also investigated antibiotic resistant genes and found antibiotics like LSM, cephalosporin, and tetracycline were significantly more abundant in AF than AM.

Whole genome sequencing of Plasmodium falciparum from dried blood spots using selective whole genome amplification.

BACKGROUND: Translating genomic technologies into healthcare applications for the malaria parasite Plasmodium falciparum has been limited by the technical and logistical difficulties of obtaining high quality clinical samples from the field. Sampling by dried blood spot (DBS) finger-pricks can be performed safely and efficiently with minimal resource and storage requirements compared with venous blood (VB). Here, the use of selective whole genome amplification (sWGA) to sequence the P. falciparum genome from clinical DBS samples was evaluated, and the results compared with current methods that use leucodepleted VB. METHODS: Parasite DNA with high (>95%) human DNA contamination was selectively amplified by Phi29 polymerase using short oligonucleotide probes of 8-12 mers as primers. These primers were selected on the basis of their differential frequency of binding the desired (P. falciparum DNA) and contaminating (human) genomes. RESULTS: Using sWGA method, clinical samples from 156 malaria patients, including 120 paired samples for head-to-head comparison of DBS and leucodepleted VB were sequenced. Greater than 18-fold enrichment of P. falciparum DNA was achieved from DBS extracts. The parasitaemia threshold to achieve >5× coverage for 50% of the genome was 0.03% (40 parasites per 200 white blood cells). Over 99% SNP concordance between VB and DBS samples was achieved after excluding missing calls. CONCLUSION: The sWGA methods described here provide a reliable and scalable way of generating P. falciparum genome sequence data from DBS samples. The current data indicate that it will be possible to get good quality sequence on most if not all drug resistance loci from the majority of symptomatic malaria patients. This technique overcomes a major limiting factor in P. falciparum genome sequencing from field samples, and paves the way for large-scale epidemiological applications.

Comparative genomic analysis of three Leishmania species that cause diverse human disease.

Leishmania parasites cause a broad spectrum of clinical disease. Here we report the sequencing of the genomes of two species of Leishmania: Leishmania infantum and Leishmania braziliensis. The comparison of these sequences with the published genome of Leishmania major reveals marked conservation of synteny and identifies only approximately 200 genes with a differential distribution between the three species. L. braziliensis, contrary to Leishmania species examined so far, possesses components of a putative RNA-mediated interference pathway, telomere-associated transposable elements and spliced leader-associated SLACS retrotransposons. We show that pseudogene formation and gene loss are the principal forces shaping the different genomes. Genes that are differentially distributed between the species encode proteins implicated in host-pathogen interactions and parasite survival in the macrophage.

Metagenomic Characterization of Poultry Cloacal and Oropharyngeal Swabs in Kenya Reveals Bacterial Pathogens and Their Antimicrobial Resistance Genes.

Poultry enteric bacterial diseases are of significant economic importance because they are responsible for production losses due to weight loss, increased morbidity and mortality, and increased cost of production arising from poor feed conversion and treatment. This cross-sectional purposive study characterized enteric bacterial pathogens in poultry from selected agroclimatic regions in Kenya and investigated their antimicrobial resistance gene profiles. Cloacal (n = 563) and oropharyngeal (n = 394) swabs were collected and pooled into 16 and 14 samples, respectively, to characterize bacterial pathogens and their antimicrobial resistance gene profiles. We report that Proteobacteria, Chlamydiae, and Firmicutes are the most dominant phyla present in both cloacal and oropharyngeal swabs of the six poultry species studied, indicating the colonization of the poultry gut by many pathogenic bacteria. Using KEGG and COG databases, some pathways related to metabolism, genetic information, and cellular processing were detected. We also report the abundance of antimicrobial resistance genes that confer resistance to ß-lactamases, aminoglycosides, and tetracycline in most of the poultry analyzed, raising concern about the dangers associated with continuous and inappropriate use of these antibiotics in poultry production. The antimicrobial resistance gene data generated in this study provides a valuable indicator of the use of antimicrobials in poultry in Kenya. The information generated is essential for managing bacterial diseases, especially in backyard poultry raised under scavenging conditions.

Widening geographic range of Rift Valley fever disease clusters associated with climate change in East Africa.

Background: Recent epidemiology of Rift Valley fever (RVF) disease in Africa suggests growing frequency and expanding geographic range of small disease clusters in regions that previously had not reported the disease. We investigated factors associated with the phenomenon by characterizing recent RVF disease events in East Africa. Methods: Data on 100 disease events (2008 - 2022) from Kenya, Uganda, and Tanzania were obtained from public databases and institutions, and modeled against possible geo-ecological risk factors of occurrence including altitude, soil type, rainfall/precipitation, temperature, normalized difference vegetation index (NDVI), livestock production system, land-use change, and long-term climatic variations. Decadal climatic variations between 1980-2022 were evaluated for association with the changing disease pattern. Results: Of 100 events, 91% were small RVF clusters with a median of one human (IQR, 1-3) and 3 livestock cases (IQR, 2-7). These clusters exhibited minimal human mortality (IQR 0-1), and occurred primarily in highlands (67%), with 35% reported in areas that had never reported RVF disease. Multivariate regression analysis of geo-ecological variables showed a positive correlation between occurrence and increasing temperature and rainfall. A 1oC increase in temperature and 1-unit increase in NDVI, 1-3 months prior were associated with increased RVF incidence rate ratios (IRR) of 1.20 (95% CI 1.1,1.2) and 9.88 (95% CI 0.85, 119.52), respectively. Long-term climatic trends showed significant decadal increase in annual mean temperature (0.12 to 0.3oC/decade, P<0.05), associated with decreasing rainfall in arid and semi-arid lowlands but increasing rainfall trends in highlands (P<0.05). These hotter and wetter highlands showed increasing frequency of RVF clusters, accounting for 76% and 43% in Uganda and Kenya, respectively. Conclusion: These findings demonstrate the changing epidemiology of RVF disease. The widening geographic range of disease is associated with climatic variations, with the likely impact of wider dispersal of virus to new areas of endemicity and future epidemics. Key questions: What is already known on this topic?: Rift Valley fever is recognized for its association with heavy rainfall, flooding, and El Niño rains in the East African region. A growing body of recent studies has highlighted a shifting landscape of the disease, marked by an expanding geographic range and an increasing number of small RVF clusters.What this study adds: This study challenges previous beliefs about RVF, revealing that it predominantly occurs in small clusters rather than large outbreaks, and its association with El Niño is not as pronounced as previously thought. Over 65% of these clusters are concentrated in the highlands of Kenya and Uganda, with 35% occurring in previously unaffected regions, accompanied by an increase in temperature and total rainfall between 1980 and 2022, along with a rise in the annual number of rainy days. Notably, the observed rainfall increases are particularly significant during the short-rains season (October-December), aligning with a secondary peak in RVF incidence. In contrast, the lowlands of East Africa, where typical RVF epidemics occur, display smaller and more varied trends in annual rainfall.How this study might affect research, practice, or policy: The worldwide consequence of the expanding RVF cluster is the broader dispersion of the virus, leading to the establishment of new regions with virus endemicity. This escalation heightens the risk of more extensive extreme-weather-associated RVF epidemics in the future. Global public health institutions must persist in developing preparedness and response strategies for such scenarios. This involves the creation and approval of human RVF vaccines and therapeutics, coupled with a rapid distribution plan through regional banks.

Widening geographic range of Rift Valley fever disease clusters associated with climate change in East Africa.

BACKGROUND: Recent epidemiology of Rift Valley fever (RVF) disease in Africa suggests growing frequency and expanding geographic range of small disease clusters in regions that previously had not reported the disease. We investigated factors associated with the phenomenon by characterising recent RVF disease events in East Africa. METHODS: Data on 100 disease events (2008-2022) from Kenya, Uganda and Tanzania were obtained from public databases and institutions, and modelled against possible geoecological risk factors of occurrence including altitude, soil type, rainfall/precipitation, temperature, normalised difference vegetation index (NDVI), livestock production system, land-use change and long-term climatic variations. Decadal climatic variations between 1980 and 2022 were evaluated for association with the changing disease pattern. RESULTS: Of 100 events, 91% were small RVF clusters with a median of one human (IQR, 1-3) and three livestock cases (IQR, 2-7). These clusters exhibited minimal human mortality (IQR, 0-1), and occurred primarily in highlands (67%), with 35% reported in areas that had never reported RVF disease. Multivariate regression analysis of geoecological variables showed a positive correlation between occurrence and increasing temperature and rainfall. A 1°C increase in temperature and a 1-unit increase in NDVI, one months prior were associated with increased RVF incidence rate ratios of 1.20 (95% CI 1.1, 1.2) and 1.93 (95% CI 1.01, 3.71), respectively. Long-term climatic trends showed a significant decadal increase in annual mean temperature (0.12-0.3°C/decade, p<0.05), associated with decreasing rainfall in arid and semi-arid lowlands but increasing rainfall trends in highlands (p<0.05). These hotter and wetter highlands showed increasing frequency of RVF clusters, accounting for 76% and 43% in Uganda and Kenya, respectively. CONCLUSION: These findings demonstrate the changing epidemiology of RVF disease. The widening geographic range of disease is associated with climatic variations, with the likely impact of wider dispersal of virus to new areas of endemicity and future epidemics.

Efficient depletion of host DNA contamination in malaria clinical sequencing.

The cost of whole-genome sequencing (WGS) is decreasing rapidly as next-generation sequencing technology continues to advance, and the prospect of making WGS available for public health applications is becoming a reality. So far, a number of studies have demonstrated the use of WGS as an epidemiological tool for typing and controlling outbreaks of microbial pathogens. Success of these applications is hugely dependent on efficient generation of clean genetic material that is free from host DNA contamination for rapid preparation of sequencing libraries. The presence of large amounts of host DNA severely affects the efficiency of characterizing pathogens using WGS and is therefore a serious impediment to clinical and epidemiological sequencing for health care and public health applications. We have developed a simple enzymatic treatment method that takes advantage of the methylation of human DNA to selectively deplete host contamination from clinical samples prior to sequencing. Using malaria clinical samples with over 80% human host DNA contamination, we show that the enzymatic treatment enriches Plasmodium falciparum DNA up to ∼9-fold and generates high-quality, nonbiased sequence reads covering >98% of 86,158 catalogued typeable single-nucleotide polymorphism loci.

Using Multiplex Amplicon PCR Technology to Efficiently and Timely Generate Rift Valley Fever Virus Sequence Data for Genomic Surveillance.

Rift Valley fever (RVF) is a febrile vector-borne disease endemic in Africa and continues to spread in new territories. It is a climate-sensitive disease mostly triggered by abnormal rainfall patterns. The disease is associated with high mortality and morbidity in both humans and livestock. RVF is caused by the Rift Valley fever virus (RVFV) of the genus Phlebovirus in the family Phenuiviridae. It is a tripartite RNA virus with three genomic segments: small (S), medium (M) and large (L). Pathogen genomic sequencing is becoming a routine procedure and a powerful tool for understanding the evolutionary dynamics of infectious organisms, including viruses. Inspired by the utility of amplicon-based sequencing demonstrated in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and Ebola, Zika and West Nile viruses, we report an RVFV sample preparation based on amplicon multiplex polymerase chain reaction (amPCR) for template enrichment and reduction of background host contamination. The technology can be implemented rapidly to characterize and genotype RVFV during outbreaks in a near-real-time manner. To achieve this, we designed 74 multiplex primer sets covering the entire RVFV genome to specifically amplify the nucleic acid of RVFV in clinical samples from an animal tissue. Using this approach, we demonstrate achieving complete RVFV genome coverage even from samples containing a relatively low viral load. We report the first primer scheme approach of generating multiplex primer sets for a tripartite virus which can be replicated for other segmented viruses.

Molecular Epidemiology and Diversity of SARS-CoV-2 in Ethiopia, 2020-2022.

Ethiopia is the second most populous country in Africa and the sixth most affected by COVID-19 on the continent. Despite having experienced five infection waves, >499,000 cases, and ~7500 COVID-19-related deaths as of January 2023, there is still no detailed genomic epidemiological report on the introduction and spread of SARS-CoV-2 in Ethiopia. In this study, we reconstructed and elucidated the COVID-19 epidemic dynamics. Specifically, we investigated the introduction, local transmission, ongoing evolution, and spread of SARS-CoV-2 during the first four infection waves using 353 high-quality near-whole genomes sampled in Ethiopia. Our results show that whereas viral introductions seeded the first wave, subsequent waves were seeded by local transmission. The B.1.480 lineage emerged in the first wave and notably remained in circulation even after the emergence of the Alpha variant. The B.1.480 was outcompeted by the Delta variant. Notably, Ethiopia's lack of local sequencing capacity was further limited by sporadic, uneven, and insufficient sampling that limited the incorporation of genomic epidemiology in the epidemic public health response in Ethiopia. These results highlight Ethiopia's role in SARS-CoV-2 dissemination and the urgent need for balanced, near-real-time genomic sequencing.

Optimizing Illumina next-generation sequencing library preparation for extremely AT-biased genomes.

BACKGROUND: Massively parallel sequencing technology is revolutionizing approaches to genomic and genetic research. Since its advent, the scale and efficiency of Next-Generation Sequencing (NGS) has rapidly improved. In spite of this success, sequencing genomes or genomic regions with extremely biased base composition is still a great challenge to the currently available NGS platforms. The genomes of some important pathogenic organisms like Plasmodium falciparum (high AT content) and Mycobacterium tuberculosis (high GC content) display extremes of base composition. The standard library preparation procedures that employ PCR amplification have been shown to cause uneven read coverage particularly across AT and GC rich regions, leading to problems in genome assembly and variation analyses. Alternative library-preparation approaches that omit PCR amplification require large quantities of starting material and hence are not suitable for small amounts of DNA/RNA such as those from clinical isolates. We have developed and optimized library-preparation procedures suitable for low quantity starting material and tolerant to extremely high AT content sequences. RESULTS: We have used our optimized conditions in parallel with standard methods to prepare Illumina sequencing libraries from a non-clinical and a clinical isolate (containing ~53% host contamination). By analyzing and comparing the quality of sequence data generated, we show that our optimized conditions that involve a PCR additive (TMAC), produces amplified libraries with improved coverage of extremely AT-rich regions and reduced bias toward GC neutral templates. CONCLUSION: We have developed a robust and optimized Next-Generation Sequencing library amplification method suitable for extremely AT-rich genomes. The new amplification conditions significantly reduce bias and retain the complexity of either extremes of base composition. This development will greatly benefit sequencing clinical samples that often require amplification due to low mass of DNA starting material.

Identification and distribution of pathogens coinfecting with Brucella spp., Coxiella burnetii and Rift Valley fever virus in humans, livestock and wildlife.

Zoonotic diseases, such as brucellosis, Q fever and Rift Valley fever (RVF) caused by Brucella spp., Coxiella burnetii and RVF virus, respectively, can have devastating effects on human, livestock, and wildlife health and cause economic hardship due to morbidity and mortality in livestock. Coinfection with multiple pathogens can lead to more severe disease outcomes and altered transmission dynamics. These three pathogens can alter host immune responses likely leading to increased morbidity, mortality and pathogen transmission during coinfection. Developing countries, such as those commonly afflicted by outbreaks of brucellosis, Q fever and RVF, have high disease burden and thus common coinfections. A literature survey provided information on case reports and studies investigating coinfections involving the three focal diseases. Fifty five studies were collected demonstrating coinfections of Brucella spp., C. burnetii or RVFV with 50 different pathogens, of which 64% were zoonotic. While the literature search criteria involved 'coinfection', only 24/55 studies showed coinfections with direct pathogen detection methods (microbiology, PCR and antigen test), while the rest only reported detection of antibodies against multiple pathogens, which only indicate a history of co-exposure, not concurrent infection. These studies lack the ability to test whether coinfection leads to changes in morbidity, mortality or transmission dynamics. We describe considerations and methods for identifying ongoing coinfections to address this critical blind spot in disease risk management.

Whole-genome sequencing of SARS-CoV-2 reveals diverse mutations in circulating Alpha and Delta variants during the first, second, and third waves of COVID-19 in South Kivu, east of the Democratic Republic of the Congo.

OBJECTIVES: We used whole-genome sequencing of SARS-CoV-2 to identify variants circulating in the Democratic Republic of the Congo and obtain molecular information useful for diagnosis, improving treatment, and general pandemic control strategies. METHODS: A total of 74 SARS-CoV-2 isolates were sequenced using Oxford Nanopore platforms. Generated reads were processed to obtain consensus genome sequences. Sequences with more than 80% genome coverage were used for variant calling, phylogenetic analysis, and classification using Pangolin lineage annotation nomenclature. RESULTS: Phylogenetic analysis based on Pangolin classification clustered South Kivu sequences into seven lineages (A.23.1, B.1.1.6, B.1.214, B.1.617.2, B.1.351, C.16, and P.1). The Delta (B.1.617.2) variant was the most dominant and responsible for outbreaks during the third wave. Based on the Wuhan reference genome, 289 distinct mutations were detected, including 141 missenses, 123 synonymous, and 25 insertions/deletions when our isolates were mapped to the Wuhan reference strain. Most of these point mutations were located within the coding sequences of the SARS-CoV-2 genome that includes spike, ORF1ab, ORF3, and nucleocapsid protein genes. The most common mutation was D614G (1841A>G) observed in 61 sequences, followed by L4715L (14143 C>T) found in 60 sequences. CONCLUSION: Our findings highlight multiple introductions of SARS-CoV-2 into South Kivu through different sources and subsequent circulation of variants in the province. These results emphasize the importance of timely monitoring of genetic variation and its effect on disease severity. This work set a foundation for the use of genomic surveillance as a tool for future global pandemic management and control.

Imported SARS-COV-2 Variants of Concern Drove Spread of Infections Across Kenya During the Second Year of the Pandemic.

Background: Using classical and genomic epidemiology, we tracked the COVID-19 pandemic in Kenya over 23 months to determine the impact of SARS-CoV-2 variants on its progression. Methods: SARS-CoV-2 surveillance and testing data were obtained from the Kenya Ministry of Health, collected daily from 306 health facilities. COVID-19-associated fatality data were also obtained from these health facilities and communities. Whole SARS-CoV-2 genome sequencing were carried out on 1241 specimens. Results: Over the pandemic duration (March 2020 - January 2022) Kenya experienced five waves characterized by attack rates (AR) of between 65.4 and 137.6 per 100,000 persons, and intra-wave case fatality ratios (CFR) averaging 3.5%, two-fold higher than the national average COVID-19 associated CFR. The first two waves that occurred before emergence of global variants of concerns (VoC) had lower AR (65.4 and 118.2 per 100,000). Waves 3, 4, and 5 that occurred during the second year were each dominated by multiple introductions each, of Alpha (74.9% genomes), Delta (98.7%), and Omicron (87.8%) VoCs, respectively. During this phase, government-imposed restrictions failed to alleviate pandemic progression, resulting in higher attack rates spread across the country. Conclusions: The emergence of Alpha, Delta, and Omicron variants was a turning point that resulted in widespread and higher SARS-CoV-2 infections across the country.

Access to ultra-long IgG CDRH3 bovine antibody sequences using short read sequencing technology.

The advances in high-throughput DNA sequencing and recombinant antibody technologies has presented new methods for characterizing antibody repertoires and significantly increased our understanding on the functional role of antibodies in immunity and their use in diagnostics, vaccine antigen design and as biological therapeutics. A subset of Bos taurus antibodies possesses unique ultra-long third complementary-determining region of the heavy chain (CDRH3) and are of special interest because they are thought to have unique functional abilities of broadly neutralizing properties - a functional role that has not been fully explored in vaccine development. Next generation sequencing technologies that are widely used to profile immunoglobulin (Ig) repertoires are based on short-read methods such as the Illumina technology. Although this technology has worked well in sequencing Ig V-D-J regions of most jawed vertebrates, it has faced serious technical challenges with sequencing regions in bovine Ig bearing ultra-long CDRH3 sequences, which are longer than 120 bp. To overcome this limitation, we have developed a sequencing strategy based on nested PCR products that allows sequence assembly of full-length bovine Ig heavy-chain (IgH) V-D-J regions. We have used this strategy to sequence IgH V-D-J regions of two Bos indicus breeds, Ankole and Boran. We confirm the presence of ultra-long CDRH3 sequences in IgG transcripts in both African cattle breeds, and provide preliminary evidence for differences and preferences in germline VH, DH and JH allele gene usage as well as differences in the length of the VH region in the two bovine breeds. Our method provides tools that should allow more robust analyses of ultra-long CDRH3 sequences aiding antibody and epitope discovery in different cattle breeds and their role in mediating immunity.

Profiling of RNA Viruses in Biting Midges (Ceratopogonidae) and Related Diptera from Kenya Using Metagenomics and Metabarcoding Analysis.

Vector-borne diseases (VBDs) cause enormous health burden worldwide, as they account for more than 17% of all infectious diseases and over 700,000 deaths each year. A significant number of these VBDs are caused by RNA virus pathogens. Here, we used metagenomics and metabarcoding analysis to characterize RNA viruses and their insect hosts among biting midges from Kenya. We identified a total of 15 phylogenetically distinct insect-specific viruses. These viruses fall into six families, with one virus falling in the recently proposed negevirus taxon. The six virus families include Partitiviridae, Iflaviridae, Tombusviridae, Solemoviridae, Totiviridae, and Chuviridae. In addition, we identified many insect species that were possibly associated with the identified viruses. Ceratopogonidae was the most common family of midges identified. Others included Chironomidae and Cecidomyiidae. Our findings reveal a diverse RNA virome among Kenyan midges that includes previously unknown viruses. Further, metabarcoding analysis based on COI (cytochrome c oxidase subunit 1 mitochondrial gene) barcodes reveal a diverse array of midge species among the insects used in the study. Successful application of metagenomics and metabarcoding methods to characterize RNA viruses and their insect hosts in this study highlights a possible simultaneous application of these two methods as cost-effective approaches to virus surveillance and host characterization. IMPORTANCE The majority of the viruses that currently cause diseases in humans and animals are RNA viruses, and more specifically arthropod-transmitted viruses. They cause diseases such as dengue, West Nile infection, bluetongue disease, Schmallenberg disease, and yellow fever, among others. Several sequencing investigations have shown us that a diverse array of RNA viruses among insect vectors remain unknown. Some of these could be ancient lineages that could aid in comprehensive studies on RNA virus evolution. Such studies may provide us with insights into the evolution of the currently pathogenic viruses. Here, we applied metagenomics to field-collected midges and we managed to characterize several RNA viruses, where we recovered complete and nearly complete genomes of these viruses. We also characterized the insect host species that are associated with these viruses. These results add to the currently known diversity of RNA viruses among biting midges as well as their associated insect hosts.