Maackia amurensis seed lectin (MASL) and soluble human podoplanin (shPDPN) sequence analysis and effects on human oral squamous cell carcinoma (OSCC) cell migration and viability.

Maackia amurensis lectins serve as research and botanical agents that bind to sialic residues on proteins. For example, M. amurensis seed lectin (MASL) targets the sialic acid modified podoplanin (PDPN) receptor to suppress arthritic chondrocyte inflammation, and inhibit tumor cell growth and motility. However, M. amurensis lectin nomenclature and composition are not clearly defined. Here, we sought to definitively characterize MASL and its effects on tumor cell behavior. We utilized SDS-PAGE and LC-MS/MS to find that M. amurensis lectins can be divided into two groups. MASL is a member of one group which is composed of subunits that form dimers, evidently mediated by a cysteine residue in the carboxy region of the protein. In contrast to MASL, members of the other group do not dimerize under nonreducing conditions. These data also indicate that MASL is composed of 4 isoforms with an identical amino acid sequence, but unique glycosylation sites. We also produced a novel recombinant soluble human PDPN receptor (shPDPN) with 17 threonine residues glycosylated with sialic acid moieties with potential to act as a ligand trap that inhibits OSCC cell growth and motility. In addition, we report here that MASL targets PDPN with very strong binding kinetics in the nanomolar range. Moreover, we confirm that MASL can inhibit the growth and motility of human oral squamous cell carcinoma (OSCC) cells that express the PDPN receptor. Taken together, these data characterize M. amurensis lectins into two major groups based on their intrinsic properties, clarify the composition of MASL and its subunit isoform sequence and glycosylation sites, define sialic acid modifications on the PDPN receptor and its ability to act as a ligand trap, quantitate MASL binding to PDPN with KD in the nanomolar range, and verify the ability of MASL to serve as a potential anticancer agent.

Benchmarking long-read aligners and SV callers for structural variation detection in Oxford nanopore sequencing data.

Structural variants (SVs) are one of the significant types of DNA mutations and are typically defined as larger-than-50-bp genomic alterations that include insertions, deletions, duplications, inversions, and translocations. These modifications can profoundly impact the phenotypic characteristics and contribute to disorders like cancer, response to treatment, and infections. Four long-read aligners and five SV callers have been evaluated using three Oxford Nanopore NGS human genome datasets in terms of precision, recall, and F1-score statistical metrics, depth of coverage, and speed of analysis. The best SV caller regarding recall, precision, and F1-score when matched with different aligners at different coverage levels tend to vary depending on the dataset and the specific SV types being analyzed. However, based on our findings, Sniffles and CuteSV tend to perform well across different aligners and coverage levels, followed by SVIM, PBSV, and SVDSS in the last place. The CuteSV caller has the highest average F1-score (82.51%) and recall (78.50%), and Sniffles has the highest average precision value (94.33%). Minimap2 as an aligner and Sniffles as an SV caller act as a strong base for the pipeline of SV calling because of their high speed and reasonable accomplishment. PBSV has a lower average F1-score, precision, and recall and may generate more false positives and overlook some actual SVs. Our results are valuable in the comprehensive evaluation of popular SV callers and aligners as they provide insight into the performance of several long-read aligners and SV callers and serve as a reference for researchers in selecting the most suitable tools for SV detection.

Complete genome sequence analysis of Bacillus velezensis A5, a promising biocontrol agent from the Pacific Ocean.

Tobacco bacterial wilt (TBW) caused by Ralstonia solanacearum is a serious soil-borne disease, which seriously damages the growth of tobacco crops. Bacillus velezensis A5 was isolated from 3000 m deep-sea sediments of the Pacific Ocean, and was found to be antagonistic to TBW. Here, we report the complete genome sequence of strain A5, which has a 4,000,699-bp single circular chromosome with 3827 genes and a G + C content of 46.44%, 87 tRNAs, and 27 rRNAs. A total of 12 gene clusters were identified in the genome of strain A5, which were responsible for the biosynthesis of antibacterial compounds, including surfactin, bacillaene, fengycin, difficidin, bacillibactin, and bacilysin. Additionally, strain A5 was found to contain a series of genes related to the biosynthesis of carbohydrate-active enzymes and secreted proteins. Our results indicate that strain A5 can be considered a promising biocontrol agent against TBW in agricultural fields.

GASOLINE: detecting germline and somatic structural variants from long-reads data.

Long-read sequencing allows analyses of single nucleic-acid molecules and produces sequences in the order of tens to hundreds kilobases. Its application to whole-genome analyses allows identification of complex genomic structural-variants (SVs) with unprecedented resolution. SV identification, however, requires complex computational methods, based on either read-depth or intra- and inter-alignment signatures approaches, which are limited by size or type of SVs. Moreover, most currently available tools only detect germline variants, thus requiring separate computation of sample pairs for comparative analyses. To overcome these limits, we developed a novel tool (Germline And SOmatic structuraL varIants detectioN and gEnotyping; GASOLINE) that groups SV signatures using a sophisticated clustering procedure based on a modified reciprocal overlap criterion, and is designed to identify germline SVs, from single samples, and somatic SVs from paired test and control samples. GASOLINE is a collection of Perl, R and Fortran codes, it analyzes aligned data in BAM format and produces VCF files with statistically significant somatic SVs. Germline or somatic analysis of 30[Formula: see text] sequencing coverage experiments requires 4-5 h with 20 threads. GASOLINE outperformed currently available methods in the detection of both germline and somatic SVs in synthetic and real long-reads datasets. Notably, when applied on a pair of metastatic melanoma and matched-normal sample, GASOLINE identified five genuine somatic SVs that were missed using five different sequencing technologies and state-of-the art SV calling approaches. Thus, GASOLINE identifies germline and somatic SVs with unprecedented accuracy and resolution, outperforming currently available state-of-the-art WGS long-reads computational methods.

Single-Cell Analysis in the Omics Era: Technologies and Applications in Cancer.

Cancer molecular profiling obtained with conventional bulk sequencing describes average alterations obtained from the entire cellular population analyzed. In the era of precision medicine, this approach is unable to track tumor heterogeneity and cannot be exploited to unravel the biological processes behind clonal evolution. In the last few years, functional single-cell omics has improved our understanding of cancer heterogeneity. This approach requires isolation and identification of single cells starting from an entire population. A cell suspension obtained by tumor tissue dissociation or hematological material can be manipulated using different techniques to separate individual cells, employed for single-cell downstream analysis. Single-cell data can then be used to analyze cell-cell diversity, thus mapping evolving cancer biological processes. Despite its unquestionable advantages, single-cell analysis produces massive amounts of data with several potential biases, stemming from cell manipulation and pre-amplification steps. To overcome these limitations, several bioinformatic approaches have been developed and explored. In this work, we provide an overview of this entire process while discussing the most recent advances in the field of functional omics at single-cell resolution.

Novel Proteoform Discovery by Precise Semi-De Novo Sequencing of Novel Junction Peptides.

Alternative splicing allows a small number of human genes to encode large amounts of proteoforms that play essential roles in normal and disease physiology. Some low-abundance proteoforms may remain undiscovered due to limited detection and analysis capabilities. Peptides coencoded by novel exons and annotated exons separated by introns are called novel junction peptides, which are the key to identifying novel proteoforms. Traditional de novo sequencing does not take into account the specificity in the composition of the novel junction peptide and is therefore not as accurate. We first developed a novel de novo sequencing algorithm, CNovo, which outperformed the mainstream PEAKS and Novor in all six test sets. We then built on CNovo to develop a semi-de novo sequencing algorithm, SpliceNovo, specifically for identifying novel junction peptides. SpliceNovo identifies junction peptides with much higher accuracy than CNovo, CJunction, PEAKS, and Novor. Of course, it is also possible to replace the built-in CNovo in SpliceNovo with other more accurate de novo sequencing algorithms to further improve its performance. We also successfully identified and validated two novel proteoforms of the human EIF4G1 and ELAVL1 genes by SpliceNovo. Our results significantly improve the ability to discover novel proteoforms through de novo sequencing.

Joint inference of exclusivity patterns and recurrent trajectories from tumor mutation trees.

Cancer progression is an evolutionary process shaped by both deterministic and stochastic forces. Multi-region and single-cell sequencing of tumors enable high-resolution reconstruction of the mutational history of each tumor and highlight the extensive diversity across tumors and patients. Resolving the interactions among mutations and recovering recurrent evolutionary processes may offer greater opportunities for successful therapeutic strategies. To this end, we present a novel probabilistic framework, called TreeMHN, for the joint inference of exclusivity patterns and recurrent trajectories from a cohort of intra-tumor phylogenetic trees. Through simulations, we show that TreeMHN outperforms existing alternatives that can only focus on one aspect of the task. By analyzing datasets of blood, lung, and breast cancers, we find the most likely evolutionary trajectories and mutational patterns, consistent with and enriching our current understanding of tumorigenesis. Moreover, TreeMHN facilitates the prediction of tumor evolution and provides probabilistic measures on the next mutational events given a tumor tree, a prerequisite for evolution-guided treatment strategies.

Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease.

Alzheimer disease (AD) is a leading cause of dementia in elderly patients who continue to live between 3 and 11 years of diagnosis. A steep rise in AD incidents is observed in the elderly population in East-Asian countries. The disease progresses through several changes, including memory loss, behavioural issues, and cognitive impairment. The etiology of AD is hard to determine because of its complex nature. The whole exome sequences of late-onset AD (LOAD) patients of Korean origin are investigated to identify rare genetic variants that may influence the complex disorder. Computational annotation was performed to assess the function of candidate variants in LOAD. The in silico pathogenicity prediction tools such as SIFT, Polyphen-2, Mutation Taster, CADD, LRT, PROVEAN, DANN, VEST3, fathmm-MKL, GERP + + , SiPhy, phastCons, and phyloP identified around 17 genes harbouring deleterious variants. The variants in the ALDH3A2 and RAD54B genes were pathogenic, while in 15 other genes were predicted to be variants of unknown significance. These variants can be potential risk candidates contributing to AD. In silico computational techniques such as molecular docking, molecular dynamic simulation and steered molecular dynamics were carried out to understand the structural insights of RAD54B with ATP. The simulation of mutant (T459N) RAD54B with ATP revealed reduced binding strength of ATP at its binding site. In addition, lower binding free energy was observed when compared to the wild-type RAD54B. Our study shows that the identified uncommon variants are linked to AD and could be probable predisposing genetic factors of LOAD.

BinderSpace: A package for sequence space analyses for datasets of affinity-selected oligonucleotides and peptide-based molecules.

Discovery of target-binding molecules, such as aptamers and peptides, is usually performed with the use of high-throughput experimental screening methods. These methods typically generate large datasets of sequences of target-binding molecules, which can be enriched with high affinity binders. However, the identification of the highest affinity binders from these large datasets often requires additional low-throughput experiments or other approaches. Bioinformatics-based analyses could be helpful to better understand these large datasets and identify the parts of the sequence space enriched with high affinity binders. BinderSpace is an open-source Python package that performs motif analysis, sequence space visualization, clustering analyses, and sequence extraction from clusters of interest. The motif analysis, resulting in text-based and visual output of motifs, can also provide heat maps of previously measured user-defined functional properties for all the motif-containing molecules. Users can also run principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) analyses on whole datasets and on motif-related subsets of the data. Functionally important sequences can also be highlighted in the resulting PCA and t-SNE maps. If points (sequences) in two-dimensional maps in PCA or t-SNE space form clusters, users can perform clustering analyses on their data, and extract sequences from clusters of interest. We demonstrate the use of BinderSpace on a dataset of oligonucleotides binding to single-wall carbon nanotubes in the presence and absence of a bioanalyte, and on a dataset of cyclic peptidomimetics binding to bovine carbonic anhydrase protein. BinderSpace is openly accessible to the public via the GitHub website: https://github.com/vukoviclab/BinderSpace.

Characterization and complete genome sequence analysis of the novel phage RPZH3 infecting Ralstonia solanacearum.

A novel lytic Ralstonia phage, RPZH3, was isolated from the soil of a tobacco field via a double agar overlay plaque assay. The phage has an icosahedral head 75 ± 5 nm in diameter with a short tail about 15 ± 5 nm in length. It was able to infect 18 out of 30 tested strains of R. solanacearum isolated from tobacco, sweet potato, tomato, pepper, and eggplant. The latent period of the phage was 80 min, and the burst period was 60 min with a burst size of about 27 pfu/cell. The phage was stable at pH 4-12 at 28°C, and it was also stable at temperatures from 45°C to 60°C at pH 7.0. The complete genome of phage RPZH3 consists of 65,958 bp, with a GC content of 64.93%. The genome contains 93 open reading frames (ORFs) and encodes a tRNA for cysteine. Nucleotide sequence alignment and phylogenetic analysis indicated that RPZH3 is a new member of the genus Gervaisevirus belonging to the class Caudoviricetes.

Multiplex MinION sequencing suggests enteric adenovirus F41 genetic diversity comparable to pre-COVID-19 era.

Human adenovirus F41 causes acute gastroenteritis in children, and has recently been associated with an apparent increase in paediatric hepatitis of unknown aetiology in the UK, with further cases reported in multiple countries. Relatively little is known about the genetic diversity of adenovirus F41 in UK children; and it is unclear what, if any, impact the COVID-19 pandemic has had on viral diversity in the UK. Methods that allow F41 to be sequenced from clinical samples without the need for viral culture are required to provide the genomic data to address these questions. Therefore, we evaluated an overlapping-amplicon method of sequencing adenovirus genomes from clinical samples using Oxford Nanopore technology. We applied this method to a small sample of adenovirus-species-F-positive extracts collected as part of standard care in the East of England region in January-May 2022. This method produced genomes with >75 % coverage in 13/22 samples and >50 % coverage in 19/22 samples. We identified two F41 lineages present in paediatric patients in the East of England in 2022. Where F41 genomes from paediatric hepatitis cases were available (n=2), these genomes fell within the diversity of F41 from the UK and continental Europe sequenced before and after the 2020-2021 phase of the COVID-19 pandemic. Our analyses suggest that overlapping amplicon sequencing is an appropriate method for generating F41 genomic data from high-virus-load clinical samples, and currently circulating F41 viral lineages were present in the UK and Europe before the COVID-19 pandemic.

Whole Exome Sequence Analysis for Inborn Errors of IL-12/IFN-γ Axis in Patient with Recurrent Typhoid Fever.

Background: The IL-12/IFN-γ axis pathways play a vital role in the control of intracellular pathogens such as Salmonella typhi. Objective: The study is aimed at using whole exome sequencing (WES) to screen out genetic defects in IL-12/IFN-γ axis in patients with recurrent typhoid fever. Methods: WES using next-generation sequencing was performed on a single patient diagnosed with recurrent typhoid fever. Following alignment and variant calling, exomes were screened for mutations in 25 genes that are involved in the IL-12/IFN-γ axis pathway. Each variant was assessed by using various bioinformatics mutational analysis tools such as SIFT, Polyphen2, LRT, MutationTaster, and MutationAssessor. Results: Out of 25 possible variations in the IL-12/IFN-γ axis genes, only 2 probable disease-causing mutations were identified. These variations were rare and include mutations in IL23R and ZNFX I. Other pathogenic mutations were found, but they were not considered likely to cause disease based on various mutation predictors. Conclusion: Applying WES to the patient with recurrent typhoid fever detects variants that are not much important as other genes in the IL-12/IFN-γ axis. Results of the current study suggest that a large population sizes would be needed to examine the functional relevance of IL-12/IFN-γ axis genes with recurrent typhoid fever.

The evolution of chikungunya virus circulating in Indonesia: Sequence analysis of the orf2 gene encoding the viral structural proteins.

Chikungunya virus (CHIKV) is an arthropod-borne virus that has caused several major epidemics globally, including in Indonesia. Although significant progress has been achieved in understanding the epidemiology and genotype circulation of CHIKV in Indonesia, the evolution of Indonesian CHIKV isolates is poorly understood. Thus, our study aimed to perform phylogenetic and mutation analyses of the orf2 gene encoding its viral structural protein to improve our understanding of CHIKV evolution in Indonesia. Complete orf2 gene sequences encoding the viral structural proteins of Indonesian-derived CHIKV were downloaded from GenBank until August 31, 2022. Various bioinformatics tools were employed to perform phylogenetic and mutation analyses of the orf2 gene. We identified 76 complete sequences of orf2 gene of CHIKV isolates originally derived from Indonesia. Maximum likelihood trees demonstrated that the majority (69/76, 90.8%) of Indonesian-derived CHIKV isolates belonged to the Asian genotype, while seven isolates (9.2%) belonged to the East/Central/South African (ECSA) genotype. The Indonesian-derived CHIKV isolates were calculated to be originated in Indonesia around 95 years ago (1927), with 95% highest posterior density (HPD) ranging from 1910 to 1942 and a nucleotide substitution rate of 5.07 × 10-4 (95% HPD: 3.59 × 10-4 to 6.67 × 10-4). Various synonymous and non-synonymous substitutions were identified in the C, E3, E2, 6K, and E1 genes. Most importantly, the E1-A226V mutation, which has been reported to increase viral adaptation in Aedes albopictus mosquitoes, was present in all ECSA isolates. To our knowledge, our study is the first comprehensive research analyzing the mutation and evolution of Indonesian-derived CHIKV based on complete sequences of the orf2 genes encoding its viral structural proteins. Our results clearly showed a dynamic evolution of CHIKV circulating in Indonesia.

Complete genome sequence analysis of a new potyvirus isolated from Paris polyphylla var. yunnanensis.

The complete genome sequence of a new potyvirus from Paris polyphylla var. yunnanensis was determined. Its genomic RNA consists of 9571 nucleotides (nt), excluding the 3'-terminal poly(A) tail, containing the typical open reading frame (ORF) of potyviruses and encoding a putative large polyprotein of 3061 amino acids. The virus shares 54.20%-59.60% nt sequence identity and 51.80%-57.90% amino acid sequence identity with other potyviruses. Proteolytic cleavage sites and conserved motifs of potyviruses were identified in the polyprotein and within individual proteins. Phylogenetic analysis indicated that the virus was most closely related to lily yellow mosaic virus. The results suggest that the virus should be classified as a member of a novel species within the genus Potyvirus, and we have tentatively named this virus "Paris yunnanensis mosaic chlorotic virus" (PyMCV).

Subtractive sequence analysis aided druggable targets mining in Burkholderia cepacia complex and finding inhibitors through bioinformatics approach.

Burkholderia cepacia complex (BCC) is a group of gram-negative bacteria composed of at least 20 different species that cause diseases in plants, animals as well as humans (cystic fibrosis and airway infection). Here, we analyzed the proteomic data of 47 BCC strains by classifying them in three groups. Phylogenetic analyses were performed followed by individual core region identification for each group. Comparative analysis of the three individual core protein fractions resulted in 1766 ortholog/proteins. Non-human homologous proteins from the core region gave 1680 proteins. Essential protein analyses reduced the target list to 37 proteins, which were further compared to a closely related out-group, Burkholderia gladioli ATCC 10,248 strain, resulting in 21 proteins. 3D structure modeling, validation, and druggability step gave six targets that were subjected to further target prioritization parameters which ultimately resulted in two BCC targets. A library of 12,000 ZINC drug-like compounds was screened, where only the top hits were selected for docking orientations. These included ZINC01405842 (against Chorismate synthase aroC) and ZINC06055530 (against Bifunctional N-acetylglucosamine-1-phosphate uridyltransferase/Glucosamine-1-phosphate acetyltransferase glmU). Finally, dynamics simulation (200 ns) was performed for each ligand-receptor complex, followed by ADMET profiling. Of these targets, details of their applicability as drug targets have not yet been elucidated experimentally, hence making our predictions novel and it is suggested that further wet-lab experimentations should be conducted to test the identified BCC targets and ZINC scaffolds to inhibit them.

Myeloma immunoglobulin rearrangement and translocation detection through targeted capture sequencing.

Multiple myeloma is a plasma cell neoplasm characterized by clonal immunoglobulin V(D)J signatures and oncogenic immunoglobulin gene translocations. Additional subclonal genomic changes are acquired with myeloma progression and therapeutic selection. PCR-based methods to detect V(D)J rearrangements can have biases introduced by highly multiplexed reactions and primers undermined by somatic hypermutation, and are not readily extended to include mutation detection. Here, we report a hybrid-capture approach (CapIG-seq) targeting the 3' and 5' ends of the V and J segments of all immunoglobulin loci that enable the efficient detection of V(D)J rearrangements. We also included baits for oncogenic translocations and mutation detection. We demonstrate complete concordance with matched whole-genome sequencing and/or PCR clonotyping of 24 cell lines and report the clonal sequences for 41 uncharacterized cell lines. We also demonstrate the application to patient specimens, including 29 bone marrow and 39 cell-free DNA samples. CapIG-seq shows concordance between bone marrow and cfDNA blood samples (both contemporaneous and follow-up) with regard to the somatic variant, V(D)J, and translocation detection. CapIG-seq is a novel, efficient approach to examining genomic alterations in myeloma.

CellMarker 2.0: an updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data.

CellMarker 2.0 (http://bio-bigdata.hrbmu.edu.cn/CellMarker or http://117.50.127.228/CellMarker/) is an updated database that provides a manually curated collection of experimentally supported markers of various cell types in different tissues of human and mouse. In addition, web tools for analyzing single cell sequencing data are described. We have updated CellMarker 2.0 with more data and several new features, including (i) Appending 36 300 tissue-cell type-maker entries, 474 tissues, 1901 cell types and 4566 markers over the previous version. The current release recruits 26 915 cell markers, 2578 cell types and 656 tissues, resulting in a total of 83 361 tissue-cell type-maker entries. (ii) There is new marker information from 48 sequencing technology sources, including 10X Chromium, Smart-Seq2 and Drop-seq, etc. (iii) Adding 29 types of cell markers, including protein-coding gene lncRNA and processed pseudogene, etc. Additionally, six flexible web tools, including cell annotation, cell clustering, cell malignancy, cell differentiation, cell feature and cell communication, were developed to analysis and visualization of single cell sequencing data. CellMarker 2.0 is a valuable resource for exploring markers of various cell types in different tissues of human and mouse.

Sequence analysis of Epstein-Barr virus RPMS1 gene in malignant hematopathy of Northern China.

The RPMS1 gene is the only member of the BamHI-A rightward transcripts (BARTs) family for which a full-length complementary DNA has been identified, and RPMS1 transcript has been confirmed in many Epstein-Barr virus (EBV)-positive malignancies. However, the effects of sequence variations of RPMS1 in hematological malignancies and their biological significance are unclear. To explore the association between RPMS1 gene variations and hematological malignancy, the RPMS1 gene of 391 EBV-positive samples from patients with EBV-positive leukemia, myelodysplastic syndromes and lymphoma in northern China were sequenced. On the basis of phylogenetic tree and mutation characteristics of RPMS1, all the sequences were divided into five major types: RPMS1-A, RPMS1-B, RPMS1-C, RPMS1-E, and RPMS1-F. RPMS1-A type, similar to the prototype B95-8, was identified in 71.87% (281/391) of samples and was the major type in all subpopulations. The frequency of RPMS1-F type was significantly higher in all malignant hematopathy groups than in healthy donors. The Hodgkin lymphoma group contained more RPMS1-F than other malignant hematopathy groups, and acute myeloid leukemia contained more RPMS1-C type than other malignant hematopathy groups. Therefore, RPMS1-A is the main type of RPMS1 gene in northern China, and RPMS1-F may be associated with hematologic malignancies.

Improving the accuracy of copolymer sequence length determination by pyrolysis gas chromatography: A comprehensive study.

Many industrial polymers which find application in contemporary materials are copolymers. Copolymers feature multiple distributions, that govern their physical properties, including the sequence distribution. Styrene-acrylate copolymers are an important class of polymers, their monomer sequence is typically determined by 13C NMR which suffers from low sensitivity and spectral resolution. A series of studies have shown that Py-GC can be applied to determine the sequence length of copolymers. The accuracy of the trimer assignments and the appropriate calibration approaches yielding reliable data have however not yet been validated. In the present study we propose a comprehensive workflow to ensure the accuracy of the sequence determination by Py-GC, next to NMR. In-depth analysis of the trimers observed in the Py-GC pyrograms of model styrene-acrylate copolymers was performed and specific MS fragments relating to the trimer sequence were assigned. A comparison of a series of copolymers yielded reliable assignments for the trimer signals. The obtained sequence lengths were in agreement with those calibrated with the benchmark method, 13C NMR. Py-GC was found to consistently underestimate the acrylate sequence length. Py-GC calibration with 13C NMR was thus found to be indispensable for the accurate absolute quantification of the sequence length by Py-GC. The calculated randomness did not vary significantly after NMR calibration, indicating that NMR calibration might not be required in all cases to obtain (relative) information on the sequence of a copolymer.

Investigation and sequence analysis of psittacine beak and feather disease virus and avian polyomavirus from companion birds in Windhoek, Namibia.

The commercial farming and trading of parrots and ornamental birds as companion animals are important economic activities in many countries. Some of the bird species farmed/traded are captured from the wild or are closely related to wild birds and therefore represent a risk of pathogen exchange/introduction. Beak and feather disease virus (BFDV) and avian poliomavirus (APV) are among the viruses with the biggest impact on companion bird populations and have been detected in different hosts worldwide. Despite their relevance for both domesticated and wild birds, our knowledge of BFDV and APV epidemiology remains limited in several African countries. In the present study, 143 cloacal swabs were collected from companion birds in Windhoek, Namibia, and tested by polymerase chain reaction for BFDV and APV. Of the samples tested, 35/143 (24.48%) tested positive for BFDV; 11/143 (7.69%) were positive for APV; and 6/143 (4.2%) tested positive for both pathogens. Positive amplicons, consisting of segments of the ORF1 and VP1 genes, were sequenced and compared with sequences from viruses identified in other countries. Four Namibian-only clades of BFDV were identified, loosely related to foreign strains, which suggest the occurrence of multiple introduction events in the past, potentially from South Africa, followed by local, independent evolution. In contrast, the Namibian APV sequences were identical to each other and form a single clade. In both instances, no correlation was observed between the sampling host and the viral phylogeny, suggesting the absence of host-specific adaptation and a remarkable, unconstrained viral circulation within Namibian borders. Therefore, while regulations and control measures developed against foreign strain introduction have proven to be effective over time, the spread of BFDV and APV within Namibia's borders appears undeterred. Additional resources should be dedicated to limit strain circulation in commercial farming facilities, markets and small-scale traders.