Biology subjects

Giansanti, A.

Publications and source records attributed to Giansanti, A..

14 recordsLinked to original sources

bioRxiv2020

Temporal evolution and adaptation of SARS-COV 2 codon usage

The outbreak of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has caused an unprecedented pandemic. Since the first sequenced whole-genome of SARS-CoV-2 on January 2020, the identification of its genetic variants has become crucial in tracking and evaluating their spread across the globe. In this study, we compared 134,905 SARS-CoV-2 genomes isolated from all affected countries since the outbreak of this novel coronavirus with the first sequenced genome in Wuhan, China to quantify the evolutionary divergence of SARS-CoV-2. Thus, we compared the codon usage patterns of SARS-CoV-2 genes encoding the membrane protein (M), envelope (E), spike surface glycoprotein (S), nucleoprotein (N), RNA-dependent RNA polymerase (RdRp). The polyproteins ORF1a and ORF1b were examined separately. We found that SARS-CoV-2 tends to diverge over time by accumulating mutations on its genome and, specifically, on the sequences encoding proteins N and S. Interestingly, different patterns of codon usage were observed among these genes. Genes S and N tend to use a narrower set of synonymous codons that are better optimized to the human host. Conversely, genes E and M consistently use the broader set of synonymous codons, which does not vary in respect to the reference genome. CAI and SiD time evolutions show a tendency to decrease that emerge for most genes. Forsdyke plots are used to study the nature of mutations and they show a rapid evolutionary divergence of each gene, due to the low values of x-intercepets.

genomics↗

bioRxiv2020

Identification of conserved epitopes in SARS-CoV-2 spike and nucleocapsid protein.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first occurred in Wuhan (China) in December 2019, is a novel virus that causes a severe acute respiratory disease. The virus spike glycoproteins and nucleocapsid proteins are the main targets for the development of vaccines and antiviral drugs, to control the disease spread. We herein study the structural order-disorder propensity and the rates of evolution of these two proteins to characterize their B cell and T cell epitopes, previously suggested to contribute to immune response caused by SARS-CoV-2 infections. We first analyzed the rates of evolution along the sequences of spike and nucleocapsid proteins in relation to the spatial locations of their epitopes. For this purpose, we compared orthologs from seven human coronaviruses: SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-229E, HCoV-OC43, HCoV-NL63, and HCoV-HKU1. We then focus on the local, structural order-disorder propensities of the protein regions where the SARS-CoV-2 epitopes are located. We show that the vast majority of nucleocapsid protein epitopes overlap the RNA-binding and dimerization domains and some of them are characterized by low rates of evolutions. Similarly, spike protein epitopes are preferentially located in regions that are predicted to be ordered and well-conserved, in correspondence of the heptad repeats 1 and 2. Interestingly, both the receptor-binding motif to ACE2 and the fusion peptide of spike protein are characterized by high rates of evolution, probably to overcome host immunity. In conclusion, our results provide evidence for conserved epitopes that may help to develop long-lasting, broad-spectrum SARS-CoV-2 vaccines.

bioinformatics↗

bioRxiv2020

Bacterial protein interaction networks: connectivityis ruled by gene conservation, essentiality andfunction

Protein-protein interaction (PPI) networks are the backbone of all processes in living cells. In this work we relate conservation, essentiality and functional repertoire of a gene to the connectivity k of the corresponding protein in the PPI networks. Focusing on a set of 42 bacterial species with reasonably separated evolutionary trajectories, we investigate three issues: i) whether the distribution of connectivity values changes between PPI subnetworks of essential and nonessential genes; ii) how gene conservation, measured both by the evolutionary retention index (ERI) and by evolutionary pressures (evaluated through the ratio Ka/Ks and ENC plots) is related to the the connectivity of the corresponding protein; iii) how PPI connectivities are modulated by evolutionary and functional relationships, as represented by the Clusters of Orthologous Proteins (COGs). We show that conservation, essentiality and functional specialization of genes control in a quite universal way the topology of the emerging bacterial PPI networks. Noteworthy, a structural transition in the network is observed such that, for connectivities k [≥] 40, bacterial PPI networks are mostly populated by genes that are conserved, essential and which, in most cases, belong to the COG cluster J, related to ribosomal functions and to the processing of genetic information.

genomics↗

bioRxiv2020

Codon usage bias in prokaryotic genomes and environmental adaptation

In each genome synonymous codons are used with different frequencies; this phenomenon is known as codon usage bias. The preferred codons tend to correspond to the most highly expressed tRNAs. It had been known that codon usage bias can influence the cellular fitness and that might be associated with the lifestyle of the organism. To test the impact of environments on genome evolution we studied the relationship between codon usage bias and the phenotypic traits of 615 prokaryotic organisms. Principal component analysis revealed that prokaryotes with a specific phenotypic characteristic and living in similar environmental conditions have similar codon preferences, accessed by the Relative Synonymous Codon Usage (RSCU), and a similar tRNA availability gauged by the tRNA gene copy number (tGCN). In addition, by measuring the average tRNA adaptation index (tAI) for each genome, we discovered that organisms able to live in multiple habitats, including facultative organisms, mesophiles and pathogenic bacteria, exhibit lower extents of translational efficiency, consistent with their need to adapt to different environments. This is the first large-scale study that examines the role of translational efficiency in the environmental adaptation of prokaryotes. Our results show that synonymous codon choices might be under strong translational selection, adapting the codons to the tRNA pool to different extents depending on the organisms lifestyle needs.

bioinformatics↗

bioRxiv2020

Co-evolution between codon usage and Protein-Protein Interaction Networks in Bacterial genomes

In this work, we study the correlation between codon usage and the network features of the PPI in bacteria genomes. We want to extend the information by Dilucca et al. (2015) about E.Colis genome for a set of other 34 bacteria. We use PCA techniques in the space of codon bias indices (compAI, compAI_w, tAI, NC) and GC content to show that genes with similar patterns of codon usage feature have a significantly higher probability that their encoded proteins interact within the PPI. And vice-versa, we show that interacting in the PPI have a coherent codon usage. This work could allow for future investigations into the possible effects that codon bias signal can have on the topology of protein interaction network and, as such, to improve existing bioinformatics methods for predicting protein interactions.

genomics↗

bioRxiv2020

New Evolutionary and Structural Insights In Plasmodium Proteins

One of the most debated topics in Evolutionary Biology concerns Low Complexity Regions of P. falciparum, the causative agent of the most virulent and deadly form of human malaria. In this work, we analysed the proteome of 22 plasmodium species including P. falciparum. SEG predicts that proteins containing Low Complexity Regions turn out to be longer than those which are predicted to be completely complex (without Low Complexity Regions). Moreover, using some well-known bioinformatics tools such as the Effective Number of Codons, the Pr2 and a new index that we have called SPI, we have noticed how proteins that embed Low Complexity Regions are under lower selective pressure than those that do not present this type of locus. By applying the Relative Synonymous Codon Usage and other tools developed ad hoc for this study, we note, instead, how the Low Complexity Regions appear to have a non-neutral codon bias with respect to the host proteins.

bioinformatics↗

bioRxiv2020

Codon usage bias in radioresistant bacteria

The relationship between patterns of codon usage bias (CUB), the preferential usage of synonimous nucleotide triplets encoding the same amino acid, and radioresistance was investigated int he genomes of 16 taxonomically distinct radioresistant prokaryotic organisms and in a control set of 11 non-radioresistant bacteria. The radioresistant species were found to be strongly biased towards G and C in the third synonimous codon position. ENC and neutrality plots also sugest that CUB in radioresistant bacteria is mainly affected by mutational bias. Furthermore, the availability of tRNA gene copy number was analyzed and it was found that nine radioresistant species have the sam number of tRNA gene copies for each codon. This suggests that tRNA gene copies and codon bias co-evolved in a specific way in radioresistant species.

molecular biology↗

bioRxiv2019

Mutations in disordered proteins as early indicators of nucleic acid changes triggering speciation

Intrinsically disordered proteins are characterized by unusual sequence composition, structural flexibility, and functional spectra. These properties play an essential role in fostering protein evolution and in the formation of complex cellular pathways, especially in multicellular organisms. In this study, we analyze the role of different structural variants of proteins in speciation processes. Firstly, we separate human and mouse proteomes (taken as a reference) in three variants of disorder: ordered proteins (ORDPs), structured proteins with intrinsically disordered protein regions (IDPRs), and intrinsically disordered proteins (IDPs). Secondly, we compare the DNA divergence with the corresponding protein divergence, by confronting human and mouse coding sequences (separated in ORDPs, IDPRs, and IDPs) with their homologs from 26 eukaryotes. As a general rule, we find that IDPs phenotypically diverge earlier than ORDPs and IDPRs. ORDPs diverge later but are phenotypically more reactive to nucleotide mutations than IDPRs and IDPs. We suggest that IDPs may be involved in the early stages of the speciation process, likely connected to their functional spectra, mainly related to nucleic acid binding and transcription factors. In contrast, ORDPs may be essential in accelerating further phenotypic divergence.

evolutionary biology↗

bioRxiv2019

Variants of intrinsic disorder: structural characterization

In a recent study, we have introduced an operational classification of the human proteome in three variants of disorder: ordered proteins (ORDPs), structured proteins with intrinsically disordered protein regions (IDPRs), intrinsically disordered proteins (IDPs). That classification was useful in functionally separating IDPRs from IDPs, which up until now have been generally considered as a whole. In this study, we corroborate this distinction by considering different physical-chemical and structural properties. Both ORDPs and IDPRs are enriched in order-promoting amino acids, whereas only IDPs show an enrichment in disordered-promoting amino acids. Consistently, ORDPs and IDPRs are preferentially located in the ordered phase of the charge-hydropathy plot, whereas IDPs are widespread over the disordered phase. We introduce the mean packing - mean pairwise energy (MP-MPE) plane to structurally characterize these variants even in the absence of a structural model. As expected for well-packed proteins, a negative linear correlation is observed between MP and MPE for ORDPs and IDPRs, whereas IDPs break this linear dependence. Finally, we find that IDPs have a more extended conformation as measured by the scaling law between the radius of gyration and the length of these proteins, and accordingly they have higher solubility and accessible surface area than ORDPs and IDPRs. Overall, our results confirm the relevance of our operational separation of IDPRs from IDPs and provide further validation of our criteria to separate IDPs from the rest of human proteome.

bioinformatics↗

bioRxiv2019

The codon frustration index as a new metric for mRNA stability, translation efficiency, and rates of protein synthesis.

Taking the human genome as a case of study, we propose a new classification of codons based only on two genomic information. We use the relative synonymous codon usage (RSCU) as a measure of non-uniform usage of synonymous codons. Similarly, we introduce here the relative gene frequencies of cognate tRNAs (RGFCt) to quantify the non-uniform availability of cognate tRNAs in each family of synonymous codons. Using these two quantities, we define two general groups of codons: non-frustrated codons, whose usage in the coding sequences is in proportion to the expected cognate tRNA levels, and frustrated codons, which do not satisfy this proportionality. With this decoding for every codon, we defined the Codon Frustration Index (CFI) as the net frustration of a gene, normalized for its length. Notably, we find that CFI correlates very well with other independent measures of CUB and a high content of non-frustrated codons increases both translation efficiency and mRNA stability. Finally, we show that genes with either a high content of frustrated or of non-frustrated codons are differentially enriched in specific functional classes that typically comprise nucleic acid binding proteins, mRNA processing factors, RNA helicase, and in several transcription factors.

bioinformatics↗

bioRxiv2019

Bacterial protein interaction networks: connectivity is ruled by gene conservation, essentiality and function

Protein-protein interaction (PPI) networks are the backbone of all processes in living cells. In this work we study how conservation, essentiality and functional repertoire of a gene relate to the connectivity k of the corresponding protein in the PPI networks. Focusing on a set of 42 mostly distantly related bacterial species, we investigate three issues: i) whether the distribution of connectivity values changes between PPI subnetworks of essential and nonessential genes; ii) how gene conservation, measured both by the evolutionary retention index (ERI) and by evolutionary pressure (as represented by the ratio Ka/Ks) is related to the the connectivity of the corresponding protein; iii) how PPI connectivities are modulated by evolutionary and functionaly relationships, as represented by the Clusters of Orthologous Proteins (COGs). We show that conservation, essentiality and functional specialization of genes control in a universal way the topology of the emerging bacterial PPI networks. Noteworthy, a structural transition in the network is observed such that, for connectivities k [≥] 40, bacterial PPI networks are mostly populated by genes that are conserved, essential and which, in most cases, belong to the COG cluster J, related to ribosomal functions and to the processing of genetic information.

systems biology↗

bioRxiv2019

Intrinsically disordered proteins and structured proteins with intrinsically disordered regions have different functional roles in the cell

Many studies about classification and the functional annotation of intrinsically disordered proteins (IDPs) are based on either the occurrence of long disordered regions or the fraction of disordered residues in the sequence. Taking into account both criteria we separate the human proteome, taken as a case study, into three variants of proteins: i) ordered proteins (ORDPs), ii) structured proteins with intrinsically disordered regions (IDPRs), and iii) intrinsically disordered proteins (IDPs). The focus of this work is on the different functional roles of IDPs and IDPRs, which up until now have been generally considered as a whole. Previous studies assigned a large set of functional roles to the general category of IDPs. We show here that IDPs and IDPRs have non-overlapping functional spectra, play different roles in human diseases, and deserve to be treated as distinct categories of proteins. IDPs enrich only a few classes, functions, and processes: nucleic acid binding proteins, chromatin binding proteins, transcription factors, and developmental processes. In contrast, IDPRs are spread over several functional protein classes and GO annotations which they partly share with ORDPs. As regards to diseases, we observe that IDPs enrich only cancer-related proteins, at variance with previous results reporting that IDPs are widespread also in cardiovascular and neurodegenerative pathologies. Overall, the operational separation of IDPRs from IDPs is relevant towards correct estimates of the occurrence of intrinsically disordered proteins in genome-wide studies and in the understanding of the functional spectra associated to different flavors of protein disorder.

bioinformatics↗

bioRxiv2018

New perspectives into the evolutionary pressures acting on the Human intrinsically disordered proteins

The codon usage bias is the well-known phenomenon of an unequal use of synonymous codons in coding DNA. These patterns reflect the action of weak selection working at the molecular level and allows to quantify the effects of natural selection, which tend to increase the fitness of the organisms. The prevailing hypothesis to explain the origin of codons usage bias is the selection-mutation-drift theory, according to which it results from a balance between the natural selection favoring optimal codons and combined action of random mutations and genetic drift which allow the persistence of nonoptimal codons. The main focus of this study is to quantify the extent of evolutionary pressures shaping the human genome. We found distinct patterns of mutational bias and natural selection in the human genes, depending on the structural properties of the encoded proteins (e.g. well-structured proteins, proteins with a long disordered segment embedded in a folded structure, or mostly unfolded proteins). Intrinsically disordered proteins are generally thought to evolve more rapidly, largely attributed to relaxed purifying selection due to the lack of structural constraint. Interestingly we observed that mostly unstructured proteins are not only affected by a basic mutational bias as the structured ones but are under a specific selective pressure underlining the important role of these proteins during evolution being freer to accept mutations, both neutral and selective. Our results provide new insight into understanding general laws and unknown aspects of protein evolution and they could be very useful in protein search and design.

evolutionary biology↗

bioRxiv2018

New Classification of Intrinsic Disorder in the Human Proteome

We propose a new, sequence-only, classification of intrinsically disordered human proteins which is based on two parameters: dr, the percentage of disordered residues, and Ld, the length of the longest disordered segment in the sequence. Depending on dr and Ld, we distinguish five variants: i) ordered proteins (ORDs); ii) not disordered proteins (NDPsj; (iii) proteins with intrinsically disordered regions (PDRs); iv) intrinsically disordered proteins (IDPs) and v) proteins with fragmented disorder (FRAGs). PDRs have been considered in the general category of intrinsically disordered proteins for a long time. We show that PDRs are closer to globular, ordered proteins (ORDs and NDPs) than to disordered ones (IDPs), both in amino acid composition and functionally. Moreover, NDPs and PDRs are uniformly spread over several functional protein classes, whereas IDPs are concentrated only on two, namely nucleic acid binding proteins and transcription factors, which are just a subset of the functions that are commonly associated with protein intrinsic disorder. As a conclusion, PDRs and IDPs should be considered, in future classifications, as distinct variants of disordered proteins, with different physical-chemical properties and functional spectra.

bioinformatics↗