CDH1 gene as biomarker towards breast cancer prediction.

Breast cancer is considered to be happened due to genetic aberration. Out of several genes expressed, it is found that cadherin 1, type 1 (CDH1) is responsible in several ways to control the metabolic order in human. Deregulation of the function of protein E-cadherin, expressed from CDH1 plays an important role in lobular breast cancer. In order to understand the root cause of this recent claim, we focus on CDH1 gene: whether the genetic information translated due to any deviation/alteration/modification in its sequence is related to the occurrence of the different types breast cancer. Towards this end, quantitative analysis of different biophysical and bio-chemical properties of CDH1 gene in genomic and proteomic levels from the available genomic (cDNA) sequences of CDH1 gene (obtained from the COSMIC Database for 78 patients, suffering from various types of breast cancer) clearly emphasizes that alternation/modification in the sequence of the CDH1 gene can be detrimental. Furthermore, Random forest, K-nearest neighbour and stochastic gradient descent (SGD) algorithms are applied on the derived dataset to classify the types of breast cancer, and to validate our hypothesis regarding the acute role of CDH1 as potential bio marker for breast cancer. Analysis of the mutated CDH1 gene sequences, and their related parameters using aforesaid machine learning techniques clearly establish that CDH1 gene can take the deterministic role in predicting the chances of occurrences of different types of breast cancer with an accuracy of >90%. Such an observation opens a new paradigm in diagnostic approach of breast cancer.Communicated by Ramaswamy H. Sarma.

Chemical characterizations of neurotransmission receptors of human and plant to unfold the evolutionary relationships among them.

Vertebrates have very well defined nervous systems. A group of researchers hypothesize that plant also has an alternative sort of sensitive nervous system. They find a close relationship of the neurotransmission mechanism of animal with that of the plant and suspect a close relationship in amino acid transport mechanism among both the organisms. Although the protein structure is conserved more than molecular sequences, but the 3D structure of protein is largely influenced by the amino acid residues in the interior part of it. The constituents of a primary protein sequence have a variety of biochemical information which control the structure, function and stability of the protein. Hence, in this present study it is tried for characterization and comparison of neurotransmission receptors associated with human and plant to unfold the evolutionary relationships among them in bio-molecular level based on the chemical properties of the amino acids. The protein sequences of ionotropic glutamate receptor and GABA receptor of human (from vertebrate) and Arabidopsis thaliana (from plant) are considered as datasets. The 20 standard amino acids are classified into 8 chemical groups and are identified by specific numeric values. Alignment-based methods are used to identify the identical and similar amino acids among the aligned sequences.The common pattern finding procedure finds some conserved regions in the receptor protein sequences of both the species. The proximity between the protein sequences are calculated based on the distribution of each chemical group (in percentage) in them and phylogenetic trees are constructed to show the evolutionary relationships of neurotransmission receptors of both the species. The conventional multiple sequence alignment (MSA) method is also applied on the datasets and the results are compared. The analysis is further extended to structural level to understand the extent to which the animal and plant proteins are similar.

Human telomerase is directly regulated by non-telomeric TRF2-G-quadruplex interaction.

Human telomerase reverse transcriptase (hTERT) remains suppressed in most normal somatic cells. Resulting erosion of telomeres leads eventually to replicative senescence. Reactivation of hTERT maintains telomeres and triggers progression of >90% of cancers. However, any direct causal link between telomeres and telomerase regulation remains unclear. Here, we show that the telomere-repeat-binding-factor 2 (TRF2) binds hTERT promoter G-quadruplexes and recruits the polycomb-repressor EZH2/PRC2 complex. This is causal for H3K27 trimethylation at the hTERT promoter and represses hTERT in cancer as well as normal cells. Two highly recurrent hTERT promoter mutations found in many cancers, including ∼83% glioblastoma multiforme, that are known to destabilize hTERT promoter G-quadruplexes, showed loss of TRF2 binding in patient-derived primary glioblastoma multiforme cells. Ligand-induced G-quadruplex stabilization restored TRF2 binding, H3K27-trimethylation, and hTERT re-suppression. These results uncover a mechanism of hTERT regulation through a telomeric factor, implicating telomere-telomerase molecular links important in neoplastic transformation, aging, and regenerative therapy.

Emerging Molecular Connections between NM23 Proteins, Telomeres and Telomere-Associated Factors: Implications in Cancer Metastasis and Ageing.

The metastasis suppressor function of NM23 proteins is widely understood. Multiple enzymatic activities of NM23 proteins have also been identified. However, relatively less known interesting aspects are being revealed from recent developments that corroborate the telomeric interactions of NM23 proteins. Telomeres are known to regulate essential physiological events such as metastasis, ageing, and cellular differentiation via inter-connected signalling pathways. Here, we review the literature on the association of NM23 proteins with telomeres or telomere-related factors, and discuss the potential implications of emerging telomeric functions of NM23 proteins. Further understanding of these aspects might be instrumental in better understanding the metastasis suppressor functions of NM23 proteins.

Characterizing genomic variants and mutations in SARS-CoV-2 proteins from Indian isolates.

SARS-CoV-2 is mutating and creating divergent variants by altering the composition of essential constituent proteins. Pharmacologically, it is crucial to understand the diverse mechanism of mutations for stable vaccine or anti-viral drug design. Our current study concentrates on all the constituent proteins of 469 SARS-CoV-2 genome samples, derived from Indian patients. However, the study may easily be extended to the samples across the globe. We perform clustering analysis towards identifying unique variants in each of the SARS-CoV-2 proteins. A total of 536 mutated positions within the coding regions of SARS-CoV-2 proteins are detected among the identified variants from Indian isolates. We quantify mutations by focusing on the unique variants of each SARS-CoV-2 protein. We report the average number of mutation per variant, percentage of mutated positions, synonymous and non-synonymous mutations, mutations occurring in three codon positions and so on. Our study reveals the most susceptible six (06) proteins, which are ORF1ab, Spike (S), Nucleocapsid (N), ORF3a, ORF7a, and ORF8. Several non-synonymous substitutions are observed to be unique in different SARS-CoV-2 proteins. A total of 57 possible deleterious amino acid substitutions are predicted, which may impact on the protein functions. Several mutations show a large decrease in protein stability and are observed in putative functional domains of the proteins that might have some role in disease pathogenesis. We observe a good number of physicochemical property change during above deleterious substitutions.

High throughput detection and genetic epidemiology of SARS-CoV-2 using COVIDSeq next-generation sequencing.

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance, and determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding, and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for the detection of SARS-CoV-2, with an additional advantage of enabling the genetic epidemiology of SARS-CoV-2.

Clade GR and clade GH isolates of SARS-CoV-2 in Asia show highest amount of SNPs.

Clades are monophyletic groups composed of a common ancestor and all its lineal descendants. As the propensity of virulence of a disease depends upon the type of clade the virus belongs to and it causes different fatality rates of disease in different countries, so the clade-wise analysis of SARS-CoV-2 isolates collected from different countries can illuminate the actual evolutionary relationships between them. In this study, 1566 SARS-CoV-2 genome sequences across ten Asian countries are collected, clustered, and characterized based on the clade they belong to. The isolates are compared to the Wuhan reference sequence" hCoV-19/Wuhan/WIV04/19″ to identify the mutations that occurred at different protein regions. Structural changes in amino acids due to mutations lead to functional instability of the proteins. Detailed clade-wise functional assessments are carried out to quantify the stability and vulnerability of the mutations occurring in SARS-CoV-2 genomes which can shade light on personalized prevention and treatment of the disease and encourage towards the invention of clade-specific vaccines.

Non-duplex G-Quadruplex DNA Structure: A Developing Story from Predicted Sequences to DNA Structure-Dependent Epigenetics and Beyond.

The story of the non-duplex DNA form known as the G-quadruplex (G4) has traversed a winding path. From initial skepticism followed by debate to a surge in interest, the G4 story intertwines many threads. Starting with computational predictions of a gene regulatory role, which now include epigenetic functions, our group was involved in many of these advances along with many other laboratories. Following a brief background, set in the latter half of the last century when the concept of the G4 as a structure took ground, here we account the developments. This is through a lens that though focused on our groups' research presents work from many other groups that played significant roles. Together these provide a broad perspective to the G4 story. Initially we were intrigued on seeing potential G4 (pG4)-forming sequences, then known to be found primarily at the telomeres and immunoglobin switch regions, occurring throughout the genome and being particularly prevalent in promoters of bacteria. We further observed that pG4s were not only prevalent but also conserved through evolution in promoters of human, chimpanzee, mouse and rat genomes. This was between 2005 and 2007. Encouraged by these partly and partly in response to the view held by many that genome-wide presence of G4s were genomic "accidents", the focus shifted to seeking experimental evidence.In the next year, 2008, two independent findings showed promise. First, on treating human cancer cells with G4-binding ligands, we observed widespread change in gene expression. Second, our search for the missing G4-specific transcription factor, without which, importantly, G4s in promoters posed only half the story, yielded results. We determined how NM23-H2 (also known as NME2 or NDPK-B) interacts with G4s and how interaction of NM23-H2 with a G4 in the promoter of the oncogene c-myc was important for regulation of c-myc transcription. NM23-H2, and subsequently many other similar factors discovered by multiple groups, is possibly giving shape to what might be the "G4-transcriptome". Later, a close look at NM23-H2-G4 interaction in regulation of the human reverse transcriptase gene (hTERT) revealed the role of G4s in local epigenetic modifications. Meanwhile work from others showed how G4s impact histone modifications following replication. Together these show the intrinsic role of DNA sequence, through formation of DNA structure, in epigenetics.More recent work, however, was waiting to reveal aspects that tend to bring forth a completely new understanding of G4s. We observed that the telomere-repeat-binding-factor-2 (TRF2), known canonically to be telomere-associated, binds extensively outside telomeres throughout the genome. Moreover, a large fraction of the non-telomeric TRF2 sites comprise G4s. Second, the extent of non-telomeric TRF2 binding at promoters was dependent on telomere length. Thereby TRF2-induced epigenetic gene regulation was telomere-dependent. Together these implicate underlying connections that show signs of addressing an intriguing unanswered question that takes us back to the beginning: Why are G4s prevalent in two distinct regions, the telomeres and gene promoters?

Mapping sequence to feature vector using numerical representation of codons targeted to amino acids for alignment-free sequence analysis.

The phylogenetic analysis based on sequence similarity targeted to real biological taxa is one of the major challenging tasks. In this paper, we propose a novel alignment-free method, CoFASA (Codon Feature based Amino acid Sequence Analyser), for similarity analysis of nucleotide sequences. At first, we assign numerical weights to the four nucleotides. We then calculate a score of each codon based on the numerical value of the constituent nucleotides, termed as degree of codons. Accordingly, we obtain the degree of each amino acid based on the degree of codons targeted towards a specific amino acid. Utilizing the degree of twenty amino acids and their relative abundance within a given sequence, we generate 20-dimensional features for every coding DNA sequence or protein sequence. We use the features for performing phylogenetic analysis of the set of candidate sequences. We use multiple protein sequences derived from Beta-globin (BG), NADH dehydrogenase subunit 5 (ND5), Transferrins (TFs), Xylanases, low identity (<40%) and high identity (⩾40%) protein sequences (encompassing 533 and 1064 protein families) for experimental assessments. We compare our results with sixteen (16) well-known methods, including both alignment-based and alignment-free methods. Various assessment indices are used, such as the Pearson correlation coefficient, RF (Robinson-Foulds) distance and ROC score for performance analysis. While comparing the performance of CoFASA with alignment-based methods (ClustalW, ClustalΩ, MAFFT, and MUSCLE), it shows very similar results. Further, CoFASA shows better performance in comparison to well-known alignment-free methods, including LZW-Kernal, jD2Stat, FFP, spaced, and AFKS-D2s in predicting taxonomic relationship among candidate taxa. Overall, we observe that the features derived by CoFASA are very much useful in isolating the sequences according to their taxonomic labels. While our method is cost-effective, at the same time, produces consistent and satisfactory outcomes.

Promise of G-Quadruplex Structure Binding Ligands as Epigenetic Modifiers with Anti-Cancer Effects.

Evidences from more than three decades of work support the function of non-duplex DNA structures called G-quadruplex (G4) in important processes like transcription and replication. In addition, G4 structures have been studied in connection with DNA base modifications and chromatin/nucleosome arrangements. Recent work, interestingly, shows promise of G4 structures, through interaction with G4 structure-interacting proteins, in epigenetics-in both DNA and histone modification. Epigenetic changes are found to be intricately associated with initiation as well as progression of cancer. Multiple oncogenes have been reported to harbor the G4 structure at regulatory regions. In this context, G4 structure-binding ligands attain significance as molecules with potential to modify the epigenetic state of chromatin. Here, using examples from recent studies we discuss the emerging role of G4 structures in epigenetic modifications and, therefore, the promise of G4 structure-binding ligands in epigenetic therapy.

NM23/NDPK proteins in transcription regulatory functions and chromatin modulation: emerging trends.

NM23/NDPK proteins have been studied for their metastasis suppressor role but the molecular pathways involved in this process are not very vivid. Nucleotide binding and kinase activities of NM23 proteins implicated in anti-metastatic effects have been widely studied. In addition to these, transcriptional regulation adds another arm to the versatility of NM23 proteins that together with the other functions may contribute to better understanding of underlying mechanisms. In this review we discuss emerging reports describing the role of NM23 proteins in gene regulation and chromatin modulation in association with other factors or on their own.