Biology subjects

Pal Choudhury, P.

Publications and source records attributed to Pal Choudhury, P..

17 recordsLinked to original sources

bioRxiv2021

Analysis of changes occurring in Codon Positions due to mutations through the cellular automata transition rules

Variation in the nucleotides of a codon may cause variations in the evolutionary patterns of a DNA or amino acid sequence. To address the capability of each position of a codon to have non-synonymous mutations, the concept of degree of mutation has been introduced. The degree of mutation of a particular position of codon defines the number of non-synonymous mutations occurring for the substitution of nucleotides at each position of a codon, when other two positions of that codon remain unaltered. A Cellular Automaton (CA), is used as a tool to model the mutations of any one of the four DNA bases A, C, T and G at a time where the DNA bases correspond to the states of the CA cells. Point mutation (substitution type) of a codon which characterizes changes in the amino acids, have been associated with local transition rules of a CA. Though there can be [Formula] transitions of a 4-state CA with 3-neighbourhood cells, here it has been possible to represent all possible point mutations of a codon in terms of combinations of 16 local transition functions of the CA. Further these rules are divided into 4 classes of equivalence. Also, according to the nature of mutations, the 16 local CA rules of substitutions are classified into 3 sets namely, No Mutation, Transition and Transversion. The experiment has been carried out with three sets of single nucleotide variations(SNVs) of three different viruses but the symptoms of the diseases caused by them are to some extent similar to each other. They are SARS-CoV-1, SARS-CoV-2 and H1N1 Type A viruses. The aim is to understand the impact of nucleotide substitutions at different positions of a codon with respect to a particular disease phenotype.

systems biology↗

bioRxiv2021

An Issue of Concern: Unique Truncated ORF8 Protein Variants of SARS-CoV-2

Open reading frame 8 (ORF8) protein is one of the most evolving accessory proteins in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). It was previously reported that the ORF8 protein inhibits presentation of viral antigens by the major histocompatibility complex class I (MHC-I) and interacts with host factors involved in pulmonary inflammation. The ORF8 protein assists SARS-CoV-2 to evade immunity and replication. Among many contributing mutations, Q27STOP, a mutation in the ORF8 protein defines the B.1.1.7 lineage of SARS-CoV-2, which is engendering the second wave of COVID-19. In the present study, 47 unique truncated ORF8 proteins (T-ORF8) due to the Q27STOP mutations were identified among 49055 available B.1.1.7 SARS-CoV-2 sequences. The results show that only one of the 47 T-ORF8 variants spread to over 57 geo-locations in North America, and other continents which includes Africa, Asia, Europe and South America. Based on various quantitative features such as amino acid homology, polar/non-polar sequence homology, Shannon entropy conservation, and other physicochemical properties of all specific 47 T-ORF8 protein variants, a collection of nine possible T-ORF8 unique variants were defined. The question of whether T-ORF8 variants work similarly to ORF8 has yet to be investigated. A positive response to the question could exacerbate future COVID-19 waves, necessitating severe containment measures.

bioinformatics↗

bioRxiv2021

Implications Derived from S-Protein Variants of SARS-CoV-2 from Six Continents

Spike (S) proteins of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are critical determinants of the infectivity and antigenicity of the virus. Several mutations in the spike protein of SARS-CoV-2 have already been detected, and their effect in immune system evasion and enhanced transmission as a cause of increased morbidity and mortality are being investigated. From pathogenic and epidemiological perspectives, spike proteins are of prime interest to researchers. This study focused on the unique variants of S proteins from six continents Asia, Africa, Europe, Oceania, South America, and North America. In comparison to the other five continents, Africa (29.065%) had the highest percentage of unique S proteins. Notably, only North America had 87% (14046) of the total (16143) specific S proteins available in the NCBI database(across all continents). Based on the amino acid frequency distributions in the S protein variants from all the continents, the phylogenetic relationship implies that unique S proteins from North America were significantly different from those of the other five continents. Overtime, the unique variants originating from North America are most likely to spread to the other geographic locations through international travel or naturally by emerging mutations. Hence it is suggested that restriction of international travel should be considered, and massive vaccination as an utmost measure to combat the spread of COVID-19 pandemic. It is also further suggested that the efficacy of existing vaccines and future vaccine development must be reviewed with careful scrutiny, and if needed, further re-engineered based on requirements dictated by new emerging S protein variants.

bioinformatics↗

bioRxiv2020

Clade GR and Clade GH Isolates 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 (Accession no:MN996528.1) 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.

systems biology↗

bioRxiv2020

Variability of Accessory Proteins Rules the SARS-CoV-2 Pathogenicity

The coronavirus disease 2019 (COVID-19) is caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) which is pandemic with an estimated fatality rate less than 1% is ongoing. SARS-CoV-2 accessory proteins ORF3a, ORF6, ORF7a, ORF7b, ORF8, and ORF10 with putative functions to manipulate host immune mechanisms such as interferons, immune signaling receptor NLRP3 (NOD-, LRR-, and pyrin domain-containing 3) inflammasome, inflammatory cytokines such as interleukin 1{beta} (IL-1{beta}) are critical in COVID-19 pathology. Outspread variations of each of the six accessory proteins of all complete proteomes (available as of October 26, 2020, in the National Center for Biotechnology Information depository) of SARS-CoV-2, were observed across six continents. Across all continents, the decreasing order of percentage of unique variations in the accessory proteins was found to be ORF3a>ORF8>ORF7a>ORF6>ORF10>ORF7b. The highest and lowest unique variations of ORF3a were observed in South America and Oceania, respectively. This finding suggests that the wide variations of accessory proteins seem to govern the pathogenicity of SARS-CoV-2, and consequently, certain propositions and recommendations can be made in the public interest.

bioinformatics↗

bioRxiv2020

Possible transmission flow of SARS-CoV-2 based on ACE2 features

Angiotensin-converting enzyme 2 (ACE2) is the cellular receptor for the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that is engendering the severe coronavirus disease 2019 (COVID-19) pandemic. The spike (S) protein receptor-binding domain (RBD) of SARS-CoV-2 binds to the three sub-domains viz. amino acids (aa) 22-42, aa 79-84, and aa 330-393 of ACE2 on human cells to initiate entry. It was reported earlier that the receptor utilization capacity of ACE2 proteins from different species, such as cats, chimpanzees, dogs, and cattle, are different. A comprehensive analysis of ACE2 receptors of nineteen species was carried out in this study, and the findings propose a possible SARS-CoV-2 transmission flow across these nineteen species.

bioinformatics↗

bioRxiv2020

Notable sequence homology of the ORF10 protein introspects the architecture of SARS-COV-2

The global public health is endangered due to COVID-19 pandemic, which is caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Despite having similar pathology to MERS and SARS-CoV, the infection fatality rate of SARS-CoV-2 is likely lower than 1%. SARS-CoV-2 has been reported to be uniquely characterized by the accessory protein ORF10, which contains eleven cytotoxic T lymphocyte (CTL) epitopes of nine amino acids length each, across various human leukocyte antigen (HLA) subtypes. In this study, all missense mutations found in sequence databases were examined across twnety-two unique SARS-CoV-2 ORF10 variants that could possibly alter viral pathogenicity. Some of these mutations decrease the stability of ORF10, e.g. I4L and V6I were found in the MoRF region of ORF10 which may also possibly contribute to Intrinsic protein disorder. Furthermore, a physicochemical and structural comparative analysis was carried out on SARS-CoV-2 and Pangolin-CoV ORF10 proteins, which share 97.37% amino acid homology. The high degree of physicochemical and structural similarity of ORF10 proteins of SARS-CoV-2 and Pangolin-CoV open questions about the architecture of SARS-CoV-2 due to the disagreement of these two ORF10 proteins over their sub-structure (loop/coil region), solubility, antigenicity and change from the strand to coil at amino acid position 26, where tyrosine is present. Altogether, SARS-CoV-2 ORF10 is a promising pharmaceutical target and a protein which should be monitored for changes which correlate to change pathogenesis and clinical course of COVID-19 infection.

bioinformatics↗

bioRxiv2020

Pathogenetic Perspective of Missense Mutations of ORF3a Protein of SARS-CoV2

One of the most important proteins for COVID-19 pathogenesis in SARS-CoV2 is the ORF3a protein which is the largest accessory protein among others accessory proteins coded by coronavirus genome. The major roles of the protein include virulence, infectivity, ion channel activity, morphogenesis and virus release. The coronavirus, SARS-CoV2 is continuously evolving naturally and thereby the encoded proteins are also mutating rapidly. Therefore, critical study of mutations in ORF3a is certainty important from the pathogenetic perspective. Here, a sum of 175 various non-synonymous mutations in the ORF3a protein of SARS-CoV2 are identified and their corresponding effects in structural stability and functions of the protein ORF3a are studied. Broadly three different classes of mutations, such as neutral, disease and mixed (neutral and disease) type mutations were observed. Consecutive mutations in some ORF3a proteins are established based on timeline of detection of mutations. Considering the amino acid compositions over the ORF3a primary protein sequences, twenty clusters are detected based on K-means clustering method. Our findings on 175 novel mutations of ORF3a proteins will extend our knowledge of ORF3a, a vital accessory protein in SARS-CoV2, which would assist to enlighten on the pathogenicity of this life-threatening COVID-19.

genomics↗

bioRxiv2020

Molecular conservation and Differential mutation on ORF3a gene in Indian SARS-CoV2 genomes

A global emergency due to the COVID-19 pandemic demands various studies related to genes and genomes of the SARS-CoV2. Among other important proteins, the role of accessory proteins are of immense importance in replication, regulation of infections of the coronavirus in the hosts. The largest accessory proteins in the SARS-CoV2 genome is ORF3a which modulates the host response to the virus infection and consequently it plays an important role in pathogenesis. In this study, an attempt is made to decipher the conservation of nucleotides, dimers, codons and amino acids in the ORF3a genes across thirty two genomes of Indian patients. ORF3a gene possesses single and double point mutations in Indian SARS-CoV2 genomes suggesting the change of SARS-CoV2s virulence property in Indian patients. We find that the parental origin of the ORF3a gene over the genomes of SARS-CoV2 and Pangolin-CoV is same from the phylogenetic analysis based on conservations of nucleotides and so on. This study highlights the accumulation of mutation on ORF3a in Indian SARS-CoV2 genomes which may provide the designing therapeutic approach against SARS-CoV2.

genomics↗

bioRxiv2020

A Numerical Representation and Classification of Codons to Investigate Codon Alternation Patterns during Genetic Mutations on Disease Pathogenesis

Alteration of amino acids is possible due to mutation in codons that could have potential reasons to occur disease. Single nucleotide substitutions (SNS) in genetic codon thus have prime importance for their ability to occur mutations that may be deleterious indeed. Effective mutation analysis can help to predict the fate of the diseased individual which can be validated later by in-vitro experiments. Hence in this present study, we try to investigate the codon alteration patterns and their impact during mutation for the genes known to be responsible for a particular disease. We use a numerical representation of four nucleotides based on the number of hydrogen bonds in their chemical structures and make a classification of 64 codons as well as corresponding 20 amino acids into three different classes (Strong, Weak and Transitional). The entire analysis has been carried out based on these classifications. For our current study, we consider two neurodegenerative diseases, Parkinsons disease, and Glaucoma. Several evidences claim similarities between both the diseases but proper pathogenetic factors are still unknown. The analysis reveals that the strong class of codons is highly mutated followed by the weak and transitional class. We observe that most of the mutations occur in the first or second positions in the codon rather than the third and mutations that occurred at the second place of codons are majorly deleterious. In most cases, the change in the determinative degree of codon due to mutation is directly proportional to the physical density property. Furthermore, we derive a determinative degree of five wild-type amino acid sequences, which can help biologists to understand the evolutionary relationship among them based on amino acid occurrence frequencies in proteins. In this regard we proposed an alignment-free method SSADDA (Sequence Similarity Analysis using Determinative Degree of Amino acid). Thus, our scheme gives a more microscopic and alternative representation of the existing codon table that helps in deciphering interesting codon alteration patterns during mutations in disease pathogenesis.

bioinformatics↗

bioRxiv2018

Comparative validation of breast cancer risk prediction models and projections for future risk stratification

BackgroundWell-validated risk models are critical for risk stratified breast cancer prevention. We used the Individualized Coherent Absolute Risk Estimation (iCARE) tool for comparative model validation of five-year risk of invasive breast cancer in a prospective cohort, and to make projections for population risk stratification.\n\nMethodsPerformance of two recently developed models, iCARE-BPC3 and iCARE-Lit, were compared with two established models (BCRAT, IBIS) based on classical risk factors in a UK-based cohort of 64,874 women (863 cases) aged 35-74 years. Risk projections in US White non-Hispanic women aged 50-70 years were made to assess potential improvements in risk stratification by adding mammographic breast density (MD) and polygenic risk score (PRS).\n\nResultsThe best calibrated models were iCARE-Lit (expected to observed number of cases (E/O)=0.98 (95% confidence interval [CI]=0.87 to 1.11)) for women younger than 50 years; and iCARE-BPC3 (E/O=1.00 (0.93 to 1.09)) for women 50 years or older. Risk projections using iCARE-BPC3 indicated classical risk factors can identify ~500,000 women at moderate to high risk (>3% five-year risk). Additional information on MD and a PRS based on 172 variants is expected to increase this to ~3.6 million, and among them, ~155,000 invasive breast cancer cases are expected within five years.\n\nConclusionsiCARE models based on classical risk factors perform similarly or better than BCRAT or IBIS. Addition of MD and PRS can lead to substantial improvements in risk stratification. Independent prospective validation of integrated models is needed prior to clinical evaluation risk stratified breast cancer screening and prevention.

epidemiology↗

bioRxiv2018

Chemical Characterization of Interacting Genes in Few Subnetworks of Alzheimer’s Disease

A number of genes have been identified as a key player in Alzheimers disease (AD). Topological analysis of co-expression network reveals that key genes are mostly central or hub genes. The association between a hub gene and its neighbour genes can be derived easily using relative abundance of their expression levels. However, it is still unexplored fact that whether any hub and its neighbour genes within a sub-network exhibits any kind of proximity with respect to their chemical properties of the DNA sequences or not, that code for a sequence of amino acids.\n\nIn this work, we try to make a quantitative investigation of the underlying biological facts in DNA sequential and primary protein level in mathematical paradigm. It may gives a holistic view of the interrelationships existing between hub genes and neighbour genes in few selective AD subnetworks. We define a mapping model from physicochemical properties of DNA sequence to chemical characterization of amino acid sequences. We use distribution of chemical groups present in a sequence after decoding into corresponding amino acids to investigate the fact that whether any hub genes are associated closely with its neighbour genes chemically in the subnetworks. Interestingly, our preliminary results confirm the fact the dependent genes that are coexpressed with its hub gene are also having proximity with respect to their amino acid chemical group distributions.\n\nCCS Concepts*Applied computing [->] Computational genomics;

synthetic biology↗

bioRxiv2018

Effective Variations of related Physicochemical Properties of Nucleotides Leading to Amino Acids for Characterizing Genes and Proteins

The aim of this paper is to make quantitative analysis of the properties which is really being carried from DNA sequence and finally landing up to the properties of a protein structure through its primary protein sequence. Thus, the paper has a theory which is applicable for any arbitrary DNA sequence whether it is of various species or mutated data or a bunch of genes responsible for a function to be occurred. Irrespective to genes of any families, species, wild type or mutated, our paper here gives a standard model which defines a mapping between physicochemical properties of any arbitrary DNA sequence and physicochemical properties of its amino acid sequence. Experiments have been carried out with PPCA protein family and its four homologs PPC(B E) which establishes that DNA sequence keeps its signature even after its translation into the corresponding amino acid sequence.

systems biology↗

bioRxiv2018

The variations of human miRNAs and Ising like base pairing models

miRNAs are small about 22-base pair long, RNA molecules are of extreme biological importance. Like other longer RNA molecules, messages in miRNAs are encoded by the permutations of only four nucleotide bases represented by A, U, C and G. However, just like words in any language, not all combination of these alphabets make a meaningful word. In fact, we find that the distributions of nucleotides bases in human miRNAs show significant deviation from randomness. First, a miRNA sequence containing four bases are mapped into a binary string with three kinds of classifications according to their chemical properties. Then, we propose a simple nearest neighbor model (Ising model) to understand the statistical variations in human miRNAs.

bioinformatics↗

bioRxiv2018

Characterizing glutamate receptor genes of Rat having vertebrate nervous system and Arabidopsis thaliana a plant having equivalent nervous system based on chemical properties of amino acids and investigating evolutionary relationships between them.

iGluR gene family of a vertebrate, Rat and AtGLR gene family of a plant, Arabidopsis thaliana [4] perform some common functionalities in neuro-transmission, which have been compared quantitatively. Our attempt is based on the chemical properties of amino acids [6, 7, 8] comprising the primary protein sequences of the aforesaid genes. 19 AtGLR genes of length varying from 808 amino acid (aa) to 1039 aa and 16 iGluR genes length varying from 902aa to 1482 aa have been taken as data sets. Thus, we detected the commonalities (conserved elements) during the long evolution of plants and animals from a common ancestor [4]. Eight different conserved regions have been found based on individual amino acids. Two different conserved regions are also found, which are based on chemical groups of amino acids. We have tried too to find different possible patterns which are common throughout the data set taken. 9 such patterns have been found with size varying from 2 to 5 amino acids at different regions in each primary protein sequences. Phylogenetic trees of AtGLR and iGluR families have also been constructed. This approach is likely to shed light on the long course of evolution.

systems biology↗

bioRxiv2017

Testing Equality of Curves After Covariate Adjustment

SO_SCPLOWUMMARYC_SCPLOWThis paper is concerned with providing simple methodological approaches for global and local tests of difference between the mean of treatment and control groups when the measured outcome is a function. The added complexity is that for every subject we have repeated samples for the same curve and additional covariates of interest. We propose a permutation based approach to test for a global difference between the averages of two functional processes after covariate adjustment. The within group averages are estimated by modeling the relationship of the functional outcome on the covariate using functional regression methods and then averaging with respect to the covariate distribution in each group. The test statistic is the L2 area under the squared difference curve. We also test for the localized differences between the two average curves using a nonparametric bootstrap of subjects to obtain the 95% pointwise and joint confidence intervals for the estimated covariate-adjusted difference curve. Extensive simulation studies illustrate that the proposed tests preserve the type one error and are highly sensitive to detecting departures from the null assumption. We illustrate our method by studying the differences in time varying oxygen consumption between the frail Interleukin 10tm1Cgn (IL10tm) mice and the wildtype mice after adjusting for body composition measures.

epidemiology↗

bioRxiv2017

Distribution of Purines and Pyrimidines over miRNAs of Human, Gorilla and Chimpanzee

Meaningful words in English need vowels to break up the sounds that consonants make. The Nature has encoded her messages in RNA molecules using only four alphabets A, U, C and G in which the nine member double-ring bases (adenine (A) and Guanine (G)) are purines, while the six member single-ring bases (cytosine (C) and uracil (U)) are pyrimidines. Four bases A, U, C and G of RNA sequences are divided into three kinds of classifications according to their chemical properties. One of the three classifications, the purine-pyrimidine class is important. In understanding the distribution (organization) of purines and pyrimidines over some of the non-coding regions of RNA, all miRNAs from three species of Family Hominidae (namely human, gorilla and chimpanzee) are considered. The distribution of purines and pyrimidines over miRNA shows deviation from randomness. Based on the quantitative metrics (fractal dimension, Hurst exponent, Hamming distance, distance pattern of purine-pyrimidine, purine-pyrimidine frequency distribution and Shannon entropy) five different clusters have been made. It is identified that there exists only one miRNA in human hsa-miR-6124 which is purely made of purine bases only.\n\nAMS Subject Classification: 92B05 & 92B15

bioinformatics↗