Native and tagged CENP-A histones are functionally inequivalent.

BACKGROUND: Over the past several decades, the use of biochemical and fluorescent tags has elucidated mechanistic and cytological processes that would otherwise be impossible. The challenging nature of certain nuclear proteins includes low abundancy, poor antibody recognition, and transient dynamics. One approach to get around those issues is the addition of a peptide or larger protein tag to the target protein to improve enrichment, purification, and visualization. However, many of these studies were done under the assumption that tagged proteins can fully recapitulate native protein function. RESULTS: We report that when C-terminally TAP-tagged CENP-A histone variant is introduced, it undergoes altered kinetochore protein binding, differs in post-translational modifications (PTMs), utilizes histone chaperones that differ from that of native CENP-A, and can partially displace native CENP-A in human cells. Additionally, these tagged CENP-A-containing nucleosomes have reduced centromeric incorporation at early G1 phase and poorly associates with linker histone H1.5 compared to native CENP-A nucleosomes. CONCLUSIONS: These data suggest expressing tagged versions of histone variant CENP-A may result in unexpected utilization of non-native pathways, thereby altering the biological function of the histone variant.

Deciphering Abdominal Aortic Diseases Through T-Cell Clonal Repertoire of Perivascular Adipose Tissue.

BACKGROUND: Recent studies suggest that immune-mediated inflammation of perivascular adipose tissue of abdominal aortic aneurysms (AAAs) contributes to disease development and progression. Whether the perivascular adipose tissue of AAA is characterized by a specific adaptive immune signature remains unknown. METHODS AND RESULTS: To investigate this hypothesis, we sequenced the T-cell receptor ß-chain in the perivascular adipose tissue of patients with AAA and compared it with patients with aortic occlusive disease, who share the former anatomical site of the lesion and risk factors but differ in pathogenic mechanisms. Our results demonstrate that patients with AAA have a lower repertoire diversity than those with aortic occlusive disease and significant differences in variable/joining gene segment usage. Furthermore, we identified a set of 7 public T-cell receptor ß-chain clonotypes that distinguished AAA and aortic occlusive disease with very high accuracy. We also found that the T-cell receptor ß-chain repertoire differentially characterizes small and large AAAs (aortic diameter<55 mm and ≥55 mm, respectively). CONCLUSIONS: This work supports the hypothesis that T cell-mediated immunity is fundamental in AAA pathogenesis and opens up new clinical perspectives.

Synergistic approach of PCR-based fragment length analysis and amplicon deep sequencing reveals rich diversity of S-alleles in sweet cherries from the Caucasian region of origin.

Introduction: The self-incompatibility system in sweet cherry (Prunus avium L.) prevents fertilization with own or genetically related pollen, and is genetically determined by the multi-allelic S-locus. Therefore, determining S-alleles is crucial for plant breeding and fruit production, as it enables the selection of compatible combinations of S-genotypes for successful pollination. Methods: In this study, S-alleles were identified in a total of 260 genotypes from the Caucasian region, the species' center of origin. S-allele genotyping was conducted using PCR fragment length analysis with the standard marker PaConsI-F/R2 and reference genotypes, complemented by sequence analysis through amplicon deep sequencing. Results and discussion: The genotypes collected from Azerbaijan and Turkey exhibit a high allelic richness at the S-locus, particularly compared to modern sweet cherry cultivars worldwide. Nine previously undescribed S-alleles were identified and designated as S45, S46, S47, S48, S49, S50, S51, S52 and S53. Given the expected high diversity for other traits, this plant material represents a valuable resource for further breeding research and introgression of new traits in future breeding programs. Furthermore, our results underscore that fragment length alone may not be sufficient for unambiguous assignment of S-alleles due to minimal length differences between different alleles. To address this issue, an S-allele reference ladder was developed using the rich diversity for precise assignment of the S-alleles. This tool can be applied in future experiments as a robust and cost-effective method for accurate S-genotyping across different runs and laboratories. Additionally, several selected S-genotypes were planted in a trial field and will be maintained as an S-allele reference collection.

Pediatric neuropathology practice in a low- and middle-income country: capacity building through institutional twinning.

Background: Accurate and precise diagnosis is central to treating central nervous system (CNS) tumors, yet tissue diagnosis is often a neglected focus in low- and middle-income countries (LMICs). Since 2016, the WHO classification of CNS tumors has increasingly incorporated molecular biomarkers into the diagnosis of CNS tumors. While this shift to precision diagnostics promises a high degree of diagnostic accuracy and prognostic precision, it has also resulted in increasing divergence in diagnostic and management practices between LMICs and high-income countries (HICs). Pathologists and laboratory professionals in LMICs lack the proper training and tools to join the molecular diagnostic revolution. We describe the impact of a 7-year long twinning program between Canada and Pakistan on pathology services. Methods: During the study period, 141 challenging cases of pediatric CNS tumors initially diagnosed at Aga Khan University Hospital (AKUH), Karachi, were sent to the Hospital for Sick Children in Toronto, Canada (SickKids), for a second opinion. Each case received histologic review and often immunohistochemical staining and relevant molecular testing. A monthly multidisciplinary online tumor board (MDTB) was conducted to discuss the results with pathologists from both institutions in attendance. Results: Diagnostic discordance was seen in 30 cases. Expert review provided subclassification for 53 cases most notably for diffuse gliomas and medulloblastoma. Poorly differentiated tumors benefited the most from second review, mainly because of the resolving power of specialized immunohistochemical stains, NanoString, and targeted gene panel next-generation sequencing. Collaboration with expert neuropathologists led to validation of over half a dozen immunostains at AKUH facilitating diagnosis of CNS tumors. Conclusions: LMIC-HIC Institutional twinning provides much-needed training and mentorship to pathologists and can help in infrastructure development by adopting and validating new immunohistochemical stains. Persistent unresolved cases indicate that molecular techniques are indispensable in for diagnosis in a minority of cases. The development of affordable alternative molecular techniques may help with these histologically unresolved cases.

The digestion and dietary carbohydrate pathway contains 100% gene mutations enrichment among 117 patients with major depressive disorder.

Introduction: Major depressive disorder (MDD) is partially inheritable while its mechanism is still uncertain. Methods: This cross-sectional study focused on gene pathways as a whole rather than polymorphisms of single genes. Deep sequencing and gene enrichment analysis based on pathways in Reactome database were obtained to reveal gene mutations. Results: A total of 117 patients with MDD and 78 healthy controls were enrolled. The Digestion and Dietary Carbohydrate pathway (Carbohydrate pathway) was determined to contain 100% mutations in patients with MDD and 0 mutation in matched healthy controls. Discussion: Findings revealed in the current study enable a better understanding of gene pathways mutations status in MDD patients, indicating a possible genetic mechanism of MDD development and a potential diagnostic or therapeutic target.

First Report of Sweet Potato Virus E(SPVE) Infecting Sweet Potato in China.

Sweet potato (Ipomoea batatas [L.] Lam.) is a versatile crop, cultivated in the subtropical and tropical areas, as food, fodder, and industrial raw material crop. In China, sweet potato has been used as a health-care food in recent years, as it contains a wide range of nutrients and xenobiotic phytochemicals. However, viral diseases are major constraint for the sweet potato yield and quality, especially the seed production and quality. Over 30 species of viruses infect sweet potato worldwide (Clark et al. 2012). More recently, a few new viruses infected sweet potato were identified, such as sweet potato virus E (SPVE), which was reported in Korea(Jo et al. 2020). In May 2022, a sweet potato sample (JSXZ1) with virus-like symptom, such as mosaic and vein clearing were collected from sweet potato germplasm Xuzhou resource nursery, Jiangsu Province, China (N34˚16', E117˚18') (Fig. S1A). To investigate the virus disease, the sample JSXZ1 showing the typical symptoms of disease was prepared for Small-RNA (sRNA) deep-sequencing. The sRNA library was constructed using TruSeq™ Small RNA Sample Prep Kits (Illumina, San Diego, USA) and sequenced using the Illumine Hiseq 2500 platform by LC-Bop Technologies (Hangzhou) CO., LTD. The sample was sequenced to obtain 26, 358, 439 raw reads and 22, 969, 139 clean reads after quality control trimming and analysis. The Velvet 1.0.5 software was used to de novo assemble the clean reads (18 to 28 nt) into larger contigs, which were then compared with the nucleotide sequences in the National Center for Biotechnology Information (NCBI) database using the BLASTn algorithm. Viruses found in the sample were sweet potato latent virus (SPLV), sweet potato feathery mottle virus (SPFMV), sweet potato chlorotic stunt virus (SPCSV), sweet potato badnavirus A (SPBV-A) and sweet potato badnavirus B (SPBV-B). Surprisingly, besides the viruses listed above, 28 contigs matched sequences of SPVE isolate GS (MH388502). To verify the result, total RNA was extracted from the sample JSXZ1 and from other leave samples (JSXZ2-JSXZ5) that contained SPFMV, SPVC, SPLV, SPVG respectively stored in lab using FastPure Universal Plant Total RNA Isolation Kit (Vazyme Biotech Co., LTD, Nanjing, China). cDNA was synthesized using random primer (hexadeoxyribonucleotide mixture; pd(N)6). The cDNA serves as template in PCR using a newly designed primer pairs based on SPVE p1 gene (SPVE-F: 5'- TCACCAAAAAGAATGCTACAAC-3'/SPVE-R: 5'-GAAATCCTCCCACTCTCCATA-3'). An expected ~500-bp PCR fragment was obtained in JSXZ1, while none of the fragment was obtained from JSXZ2-JSXZ5 (Fig. S1B). The PCR fragment was cloned into pMD18-T vector (Takara Bio Inc., Beijing, China) and plasmid DNA from transformed Escherichia coli DH5α cell (n=3) were commercially sequenced by Sangon Biotech (Shanghai) Co., Ltd. The sequences of the three fragment clones we obtained were 100% identical when compared. A BLASTN analysis of the sequences revealed that they are specific to SPVE and shared 98.62% nucleotide identity to SPVE GS isolate (MH388502) and one sequence was submitted to GenBank (Accession number OQ948331). To determine the occurrence of SPVE in infected sweet potato plants, a total of 37 leaves samples with viral symptom collected from Shandong Province (n=6) and Jiangsu Province (n=31) were indexed by RT-PCR as described before. Only 9 (24.3%) out of 37 from Shandong (n=1) and Jiangsu (n=8) were positive to SPVE respectively. In addition, five additional viruses (SPFMV, SPVC, SPVG, SPLV, SPCSV) were detected among these 37 samples and always in a mixed infection of two or more viruses. To our knowledge, this is the first report of SPVE infecting sweet potato in China. Sweet potato is an important crop in China and other countries (Zhang et al. 2023). China is the largest sweet potato producer all over the world. In addition, as sweet potato is produced through the vegetative propagation mode, thus, more attention should be paid to detection and monitoring of occurrence of SPVE in China.

Global and single-nucleotide resolution detection of 7-methylguanosine in RNA.

RNA modifications, including N-7-methylguanosine (m7G), are pivotal in governing RNA stability and gene expression regulation. The accurate detection of internal m7G modifications is of paramount significance, given recent associations between altered m7G deposition and elevated expression of the methyltransferase METTL1 in various human cancers. The development of robust m7G detection techniques has posed a significant challenge in the field of epitranscriptomics. In this study, we introduce two methodologies for the global and accurate identification of m7G modifications in human RNA. We introduce borohydride reduction sequencing (Bo-Seq), which provides base resolution mapping of m7G modifications. Bo-Seq achieves exceptional performance through the optimization of RNA depurination and scission, involving the strategic use of high concentrations of NaBH4, neutral pH and the addition of 7-methylguanosine monophosphate (m7GMP) during the reducing reaction. Notably, compared to NaBH4-based methods, Bo-Seq enhances the m7G detection performance, and simplifies the detection process, eliminating the necessity for intricate chemical steps and reducing the protocol duration. In addition, we present an antibody-based approach, which enables the assessment of m7G relative levels across RNA molecules and biological samples, however it should be used with caution due to limitations associated with variations in antibody quality between batches. In summary, our novel approaches address the pressing need for reliable and accessible methods to detect RNA m7G methylation in human cells. These advancements hold the potential to catalyse future investigations in the critical field of epitranscriptomics, shedding light on the complex regulatory roles of m7G in gene expression and its implications in cancer biology.

Genotyping Plasmodium falciparum gametocytes using amplicon deep sequencing.

BACKGROUND: Understanding the dynamics of gametocyte production in polyclonal Plasmodium falciparum infections requires a genotyping method that detects distinct gametocyte clones and estimates their relative frequencies. Here, a marker was identified and evaluated to genotype P. falciparum mature gametocytes using amplicon deep sequencing. METHODS: A data set of polymorphic regions of the P. falciparum genome was mined to identify a gametocyte genotyping marker. To assess marker resolution, the number of unique haplotypes in the marker region was estimated from 95 Malawian P. falciparum whole genome sequences. Specificity of the marker for detection of mature gametocytes was evaluated using reverse transcription-polymerase chain reaction of RNA extracted from NF54 mature gametocytes and rings from a non-gametocyte-producing strain of P. falciparum. Amplicon deep sequencing was performed on experimental mixtures of mature gametocytes from two distinct parasite clones, as well as gametocyte-positive P. falciparum field isolates to evaluate the quantitative ability and determine the limit of detection of the genotyping approach. RESULTS: A 400 bp region of the pfs230 gene was identified as a gametocyte genotyping marker. A larger number of unique haplotypes was observed at the pfs230 marker (34) compared to the sera-2 (18) and ama-1 (14) markers in field isolates from Malawi. RNA and DNA genotyping accurately estimated gametocyte and total parasite clone frequencies when evaluating agreement between expected and observed haplotype frequencies in gametocyte mixtures, with concordance correlation coefficients of 0.97 [95% CI: 0.92-0.99] and 0.92 [95% CI: 0.83-0.97], respectively. The detection limit of the genotyping method for male gametocytes was 0.41 pfmget transcripts/µl [95% CI: 0.28-0.72] and for female gametocytes was 1.98 ccp4 transcripts/µl [95% CI: 1.35-3.68]. CONCLUSIONS: A region of the pfs230 gene was identified as a marker to genotype P. falciparum gametocytes. Amplicon deep sequencing of this marker can be used to estimate the number and relative frequency of parasite clones among mature gametocytes within P. falciparum infections. This gametocyte genotyping marker will be an important tool for studies aimed at understanding dynamics of gametocyte production in polyclonal P. falciparum infections.

GMMA Can Stabilize Proteins Across Different Functional Constraints.

Stabilizing proteins without otherwise hampering their function is a central task in protein engineering and design. PYR1 is a plant hormone receptor that has been engineered to bind diverse small molecule ligands. We sought a set of generalized mutations that would provide stability without affecting functionality for PYR1 variants with diverse ligand-binding capabilities. To do this we used a global multi-mutant analysis (GMMA) approach, which can identify substitutions that have stabilizing effects and do not lower function. GMMA has the added benefit of finding substitutions that are stabilizing in different sequence contexts and we hypothesized that applying GMMA to PYR1 with different functionalities would identify this set of generalized mutations. Indeed, conducting FACS and deep sequencing of libraries for PYR1 variants with two different functionalities and applying a GMMA analysis identified 5 substitutions that, when inserted into four PYR1 variants that each bind a unique ligand, provided an increase of 2-6 °C in thermal inactivation temperature and no decrease in functionality.

SARS-CoV-2 mutant spectra as variant of concern nurseries: endless variation?

Introduction: SARS-CoV-2 isolates of a given clade may contain low frequency genomes that encode amino acids or deletions which are typical of a different clade. Methods: Here we use high resolution ultra-deep sequencing to analyze SARS-CoV-2 mutant spectra. Results: In 6 out of 11 SARS-CoV-2 isolates from COVID-19 patients, the mutant spectrum of the spike (S)-coding region included two or more amino acids or deletions, that correspond to discordant viral clades. A similar observation is reported for laboratory populations of SARS-CoV-2 USA-WA1/2020, following a cell culture infection in the presence of remdesivir, ribavirin or their combinations. Moreover, some of the clade-discordant genome residues are found in the same haplotype within an amplicon. Discussion: We evaluate possible interpretations of these findings, and reviewed precedents for rapid selection of genomes with multiple mutations in RNA viruses. These considerations suggest that intra-host evolution may be sufficient to generate minority sequences which are closely related to sequences typical of other clades. The results provide a model for the origin of variants of concern during epidemic spread─in particular Omicron lineages─that does not require prolonged infection, involvement of immunocompromised individuals, or participation of intermediate, non-human hosts.

Molecular detection of exosomal miRNAs of blood serum for prognosis of colorectal cancer.

Colorectal cancer (CRC) is the third most common cancer affecting people. The discovery of new, non-invasive, specific, and sensitive molecular biomarkers for CRC may assist in the diagnosis and support therapeutic decision making. Exosomal miRNAs have been demonstrated in carcinogenesis and CRC development, which makes these miRNAs strong biomarkers for CRC. Deep sequencing allows a robust high-throughput informatics investigation of the types and abundance of exosomal miRNAs. Thus, exosomal miRNAs can be efficiently examined as diagnostic biomarkers for disease screening. In the present study, a number of 660 mature miRNAs were detected in patients diagnosed with CRC at different stages. Of which, 29 miRNAs were differentially expressed in CRC patients compared with healthy controls. Twenty-nine miRNAs with high abundance levels were further selected for subsequent analysis. These miRNAs were either highly up-regulated (e.g., let-7a-5p, let-7c-5p, let-7f-5p, let-7d-3p, miR-423-5p, miR-3184-5p, and miR-584) or down-regulated (e.g., miR-30a-5p, miR-99-5p, miR-150-5p, miR-26-5p and miR-204-5p). These miRNAs influence critical genes in CRC, leading to either tumor growth or suppression. Most of the reported diagnostic exosomal miRNAs were shown to be circulating in blood serum. The latter is a novel miRNA that was found in exosomal profile of blood serum. Some of the predicted target genes of highly expressed miRNAs participate in several cancer pathways, including CRC pathway. These target genes include tumor suppressor genes, oncogenes and DNA repair genes. Main focus was given to multiple critical signaling cross-talking pathways including transforming growth factor ß (TGFß) signaling pathways that are directly linked to CRC. In conclusion, we recommend further analysis in order to experimentally confirm exact relationships between selected differentially expressed miRNAs and their predicted target genes and downstream functional consequences.

Profiling of Groundnut bud necrosis orthotospovirus-responsive microRNA and their targets in tomato based on deep sequencing.

Tomato, an extensively cultivated vegetable crop produces miRNAs in response to infection with Groundnut bud necrosis orthotospovirus, a viral pathogen causing significant economic losses. High-throughput miRNA sequencing was performed on tomato leaves inoculated with GBNV and mock-inoculated leaves as controls. Analysis revealed 73 known miRNAs belonging to 24 miRNA families, with variable expression levels. Interestingly, 39 miRNAs were upregulated, and 34 were downregulated in response to GBNV infection. Stem-loop quantitative reverse transcription PCR validated the differential expression of selected miRNAs. Additionally, 30 miRNA encoded proteins were identified to be involved in disease resistance and susceptibility. The miRNA-target interactions were found to play significant roles in cellular and metabolic activities, as well as modulating signaling pathways during the plant-virus interaction. The findings shed light on the intricate regulatory network of miRNAs in tomato response to viral infection and may contribute to developing strategies for improving crop protection against viral diseases.

Identification of a lncRNA/circRNA-miRNA-mRNA network in Nasopharyngeal Carcinoma by deep sequencing and bioinformatics analysis.

Background: Accumulating evidence indicates that non-coding RNAs (ncRNA), including long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), can function as competitive endogenous RNAs (ceRNAs) by binding to microRNAs (miRNAs) and regulating host gene expression at the transcriptional or post-transcriptional level. Dysregulation in ceRNA network regulation has been implicated in the occurrence and development of cancer. However, the lncRNA/circRNA-miRNA-mRNA regulatory network is still lacking in nasopharyngeal carcinoma (NPC). Methods: Differentially expressed genes (DEGs) were obtained from our previous sequencing data and Gene Expression Omnibus (GEO). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) were used to explore the biological functions of these common DEGs. Through a series of bioinformatic analyses, the lncRNA/circRNA-miRNA-mRNA network was established. In additional, the external data GSE102349 was used to test the prognostic value of the hub mRNAs through the Kaplan-Meier method. Results: We successfully constructed a lncRNA/circRNA-miRNA-mRNA network in NPC, consisting of 16 lncRNAs, 6 miRNAs, 3 circRNAs and 10 mRNAs and found that three genes (TOP2A, ZWINT, TTK) were significantly associated with overall survival time (OS) in patients. Conclusion: The regulatory network revealed in this study may help comprehensively elucidate the ceRNA mechanisms driving NPC, and provide novel candidate biomarkers for evaluating the prognosis of NPC.

The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design.

Synthetic antibodies (Abs) represent a category of artificial proteins capable of closely emulating the functions of natural Abs. Their in vitro production eliminates the need for an immunological response, streamlining the process of Ab discovery, engineering, and development. These artificially engineered Abs offer novel approaches to antigen recognition, paratope site manipulation, and biochemical/biophysical enhancements. As a result, synthetic Abs are fundamentally reshaping conventional methods of Ab production. This mirrors the revolution observed in molecular biology and genomics as a result of deep sequencing, which allows for the swift and cost-effective sequencing of DNA and RNA molecules at scale. Within this framework, deep sequencing has enabled the exploration of whole genomes and transcriptomes, including particular gene segments of interest. Notably, the fusion of synthetic Ab discovery with advanced deep sequencing technologies is redefining the current approaches to Ab design and development. Such combination offers opportunity to exhaustively explore Ab repertoires, fast-tracking the Ab discovery process, and enhancing synthetic Ab engineering. Moreover, advanced computational algorithms have the capacity to effectively mine big data, helping to identify Ab sequence patterns/features hidden within deep sequencing Ab datasets. In this context, these methods can be utilized to predict novel sequence features thereby enabling the successful generation of de novo Ab molecules. Hence, the merging of synthetic Ab design, deep sequencing technologies, and advanced computational models heralds a new chapter in Ab discovery, broadening our comprehension of immunology and streamlining the advancement of biological therapeutics.

In silico approach for the identification of tRNA-derived small non-coding RNAs in SARS-CoV infection.

tsRNAs (tRNA-derived small non-coding RNAs), including tRNA halves (tiRNAs) and tRNA fragments (tRFs), have been implicated in some viral infections, such as respiratory viral infections. However, their involvement in SARS-CoV infection is completely unknown. A comprehensive analysis was performed to determine tsRNA populations in a mouse model of SARS-CoV-infected samples containing the wild-type and attenuated viruses. Data from the Gene Expression Omnibus (GEO) dataset at NCBI (accession ID GSE90624 ) was used for this study. A count matrix was generated for the tRNAs. Differentially expressed tRNAs, followed by tsRNAs derived from each significant tRNAs at different conditions and time points between the two groups WT(SARS-CoV-MA15-WT) vs Mock and ΔE (SARS-CoV-MA15-ΔE) vs Mock were identified. Notably, significantly differentially expressed tRNAs at 2dpi but not at 4dpi. The tsRNAs originating from differentially expressed tRNAs across all the samples belonging to each condition (WT, ΔE, and Mock) were identified. Intriguingly, tRFs (tRNA-derived RNA fragments) exhibited higher levels compared to tiRNAs (tRNA-derived stress-induced RNAs) across all samples associated with WT SARS-CoV strain compared to ΔE and mock-infected samples. This discrepancy suggests a non-random formation of tsRNAs, hinting at a possible involvement of tsRNAs in SARS-CoV viral infection.

Improved detection of low-frequency within-host variants from deep sequencing: A case study with human papillomavirus.

High-coverage sequencing allows the study of variants occurring at low frequencies within samples, but is susceptible to false-positives caused by sequencing error. Ion Torrent has a very low single nucleotide variant (SNV) error rate and has been employed for the majority of human papillomavirus (HPV) whole genome sequences. However, benchmarking of intrahost SNVs (iSNVs) has been challenging, partly due to limitations imposed by the HPV life cycle. We address this problem by deep sequencing three replicates for each of 31 samples of HPV type 18 (HPV18). Errors, defined as iSNVs observed in only one of three replicates, are dominated by C→T (G→A) changes, independently of trinucleotide context. True iSNVs, defined as those observed in all three replicates, instead show a more diverse SNV type distribution, with particularly elevated C→T rates in CCG context (CCG→CTG; CGG→CAG) and C→A rates in ACG context (ACG→AAG; CGT→CTT). Characterization of true iSNVs allowed us to develop two methods for detecting true variants: (1) VCFgenie, a dynamic binomial filtering tool which uses each variant's allele count and coverage instead of fixed frequency cut-offs; and (2) a machine learning binary classifier which trains eXtreme Gradient Boosting models on variant features such as quality and trinucleotide context. Each approach outperforms fixed-cut-off filtering of iSNVs, and performance is enhanced when both are used together. Our results provide improved methods for identifying true iSNVs in within-host applications across sequencing platforms, specifically using HPV18 as a case study.

The use of next-generation sequencing in personalized medicine.

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

The Role of HIV-1-Encoded microRNAs in Viral Replication.

microRNAs (miRNAs) are small non-coding RNAs (sncRNAs) that play an important role in the life cycle of human viruses. We sought to characterize human immunodeficiency virus 1 (HIV-1)-encoded miRNAs and determine their role in viral replication. Initially, a bioinformatic analysis was used to predict HIV-1-encoded miRNAs. Next, a representative number of these predicted sequences were verified using a miRNA microarray chip, reverse transcription PCR (RT-PCR), and the deep sequencing of RNA extracted from HIV-1-infected cells. Eight HIV-1-encoded sncRNA sequences conforming to the criteria that define miRNAs were identified in HIV-1-infected immortalized T cells and human primary CD4+ lymphocytes; five of the eight sequences have not been previously reported. Deep sequencing validated the presence of these virus-encoded miRNA sequences and uncovered large numbers of atypical sncRNA sequences, lacking characteristics of conventional miRNAs. We named these sequences small RNAs (smRNAs). The overexpression of four candidate HIV-1-encoded miRNAs and silencing of two smRNAs significantly increased HIV-1 viral replication. Our study uncovered novel HIV-1-encoded sncRNAs that, upon deregulated expression, alter viral titers in HIV-1-infected cells, suggesting that miRNAs and smRNAs play an important role in regulating viral replication. Future studies may reveal the function of HIV-1-encoded sncRNAs and their possible implications for diagnosis and treatment.

A Deep Sequencing Strategy for Investigation of Virus Variants within African Swine Fever Virus-Infected Pigs.

African swine fever virus (ASFV) is the causative agent of African swine fever, an economically important disease of pigs, often with a high case fatality rate. ASFV has demonstrated low genetic diversity among isolates collected within Eurasia. To explore the influence of viral variants on clinical outcomes and infection dynamics in pigs experimentally infected with ASFV, we have designed a deep sequencing strategy. The variant analysis revealed unique SNPs at <10% frequency in several infected pigs as well as some SNPs that were found in more than one pig. In addition, a deletion of 10,487 bp (resulting in the complete loss of 21 genes) was present at a nearly 100% frequency in the ASFV DNA from one pig at position 6362-16849. This deletion was also found to be present at low levels in the virus inoculum and in two other infected pigs. The current methodology can be used for the currently circulating Eurasian ASFVs and also adapted to other ASFV strains and genotypes. Comprehensive deep sequencing is critical for following ASFV molecular evolution, especially for the identification of modifications that affect virus virulence.

Revolutionizing Synthetic Antibody Design: Harnessing Artificial Intelligence and Deep Sequencing Big Data for Unprecedented Advances.

Synthetic antibodies (Abs) represent a category of engineered proteins meticulously crafted to replicate the functions of their natural counterparts. Such Abs are generated in vitro, enabling advanced molecular alterations associated with antigen recognition, paratope site engineering, and biochemical refinements. In a parallel realm, deep sequencing has brought about a paradigm shift in molecular biology. It facilitates the prompt and cost-effective high-throughput sequencing of DNA and RNA molecules, enabling the comprehensive big data analysis of Ab transcriptomes, including specific regions of interest. Significantly, the integration of artificial intelligence (AI), based on machine- and deep- learning approaches, has fundamentally transformed our capacity to discern patterns hidden within deep sequencing big data, including distinctive Ab features and protein folding free energy landscapes. Ultimately, current AI advances can generate approximations of the most stable Ab structural configurations, enabling the prediction of de novo synthetic Abs. As a result, this manuscript comprehensively examines the latest and relevant literature concerning the intersection of deep sequencing big data and AI methodologies for the design and development of synthetic Abs. Together, these advancements have accelerated the exploration of antibody repertoires, contributing to the refinement of synthetic Ab engineering and optimizations, and facilitating advancements in the lead identification process.