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Genome heterogeneity drives the evolution of species
[article]
2019
arXiv
pre-print
Preserved Fulltext
Most of the DNA that composes a complex organism is non-coding and defined as junk. Even the coding part is composed of genes that affect the phenotype differently. Therefore, a random mutation has an effect on the specimen fitness that strongly depends on the DNA region where it occurs. Such heterogeneous composition should be linked to the evolutionary process. However, the way is still unknown. Here, we study a minimal model for the evolution of an ecosystem where two antagonist species
arXiv:1912.01444v1
fatcat:a2pzuwncj5h7vfvmnp6qnaflde
more »
... gle for survival on a lattice. Each specimen possesses a toy genome, encoding for its phenotype. The gene pool of populations changes in time due to the effect of random mutations on genes (entropic force) and of interactions with the environment and between individuals (natural selection). We prove that the relevance of each gene in the manifestation of the phenotype is a key feature for evolution. In the presence of a uniform gene relevance, a mutational meltdown is observed. Natural selection acts quenching the ecosystem in a non-equilibriumstate that slowly drifts, decreasing the fitness and leading to the extinction of the species. Conversely, if a specimen is provided with a heterogeneous gene relevance, natural selection wins against entropic forces, and the species evolves increasing its fitness. We finally show that heterogeneity together with spatial correlations is responsible for spontaneous sympatric speciation.
Competing endogenous RNA crosstalk at system level
[article]
2019
arXiv
pre-print
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microRNAs (miRNAs) regulate gene expression at post-transcriptional level by repressing target RNA molecules. Competition to bind miRNAs tends in turn to correlate their targets, establishing effective RNA-RNA interactions that can influence expression levels, buffer fluctuations and promote signal propagation. Such a potential has been characterized mathematically for small motifs both at steady state and away from stationarity. Experimental evidence, on the other hand, suggests that competing
arXiv:1910.09256v1
fatcat:3pzszz2om5celiyvkdwawhvylq
more »
... endogenous RNA (ceRNA) crosstalk is rather weak. Extended miRNA-RNA networks could however favour the integration of many crosstalk interactions, leading to significant large-scale effects in spite of the weakness of individual links. To clarify the extent to which crosstalk is sustained by the miRNA interactome, we have studied its emergent systemic features in silico in large-scale miRNA-RNA network reconstructions. We show that, although generically weak, system-level crosstalk patterns (i) are enhanced by transcriptional heterogeneities, (ii) can achieve high-intensity even for RNAs that are not co-regulated, (iii) are robust to variability in transcription rates, and (iv) are significantly non-local, i.e. correlate weakly with miRNA-RNA interaction parameters. Furthermore, RNA levels are generically more stable when crosstalk is strongest. As some of these features appear to be encoded in the network's topology, crosstalk may functionally be favoured by natural selection. These results suggest that, besides their repressive role, miRNAs mediate a weak but resilient and context-independent network of cross-regulatory interactions that interconnect the transcriptome, stabilize expression levels and support system-level responses.
Entropy evaluation sheds light on ecosystem complexity
[article]
2018
arXiv
pre-print
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Preserving biodiversity and ecosystem stability is a challenge that can be pursued through modern statistical mechanics modeling. Here we introduce a variational maximum entropy-based algorithm to evaluate the entropy in a minimal ecosystem on a lattice in which two species struggle for survival. The method quantitatively reproduces the scale-free law of the prey shoals size, where the simpler mean-field approach fails: the direct near neighbor correlations are found to be the fundamental
arXiv:1803.11524v1
fatcat:nfvmudvfrvf3hheyakvq4rot3a
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... ient describing the system self-organized behavior. Furthermore, entropy allows the measurement of structural ordering, that is found to be a key ingredient in characterizing two different coexistence behaviors, one where predators form localized patches in a sea of preys and another where species display more complex patterns. The general nature of the introduced method paves the way for its application in many other systems of interest.
Genome heterogeneity drives the evolution of species
2020
Physical Review Research
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Most of the DNA that composes a complex organism is noncoding and defined as junk. Even the coding part is composed of genes that affect the phenotype differently. Therefore a random mutation has an effect on the specimen fitness that strongly depends on the DNA region where it occurs. Understanding how this heterogeneous composition influences the fitness evolution of individuals is hampered by the complexity of the problem and a clear picture is missing. Here we study a minimal model for the
doi:10.1103/physrevresearch.2.043026
fatcat:lqteppxmvbez3nspbb23osfnqu
more »
... volution of an ecosystem where two antagonist species struggle for survival on a lattice. Each specimen has a unique toy genome that codes for its phenotype. The gene pool of populations changes in time due to the effect of random mutations on genes (entropic force) and of interactions with the environment and between individuals (natural selection). We prove that the relevance of each gene in the manifestation of the phenotype is a key feature for evolution. In the presence of a uniform gene relevance, a mutational meltdown is observed. Natural selection acts to quench the ecosystem in a nonequilibrium state that slowly drifts, decreasing the fitness and leading to the extinction of the species. Conversely, if a specimen is provided with a heterogeneous gene relevance, natural selection wins against entropic forces and the species evolves, increasing its fitness. We finally show that heterogeneity together with spatial correlations are responsible for spontaneous sympatric speciation.
Asymmetric Binomial Statistics Explains Organelle Partitioning Variance in Cancer Cell Proliferation
[article]
2021
bioRxiv
pre-print
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Miotto, M. & Monacelli, L. Genome heterogeneity drives the evolution of species. Phys. Rev. Research 2, 043026 (2020). 10. Elowitz, M. B. Stochastic gene expression in a single cell. ...
doi:10.1101/2021.01.21.427596
fatcat:k7ck452vzrcqtjmoqtyrl7g3ra
Molecular mechanisms behind anti SARS-CoV-2 action of lactoferrin
[article]
2020
arXiv
pre-print
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Despite the huge effort to contain the infection, the novel SARS-CoV-2 coronavirus has rapidly become pandemics, mainly due to its extremely high human-to-human transmission capability, and a surprisingly high viral charge of symptom-less people. While the seek of a vaccine is still ongoing, promising results have been obtained with antiviral compounds. In particular, lactoferrin is found to have beneficial effects both in preventing and soothing the infection. Here, we explore the possible
arXiv:2007.07341v1
fatcat:b2rl6sabgbbntdskue2zq7no6m
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... cular mechanisms with which lactoferrin interferes with SARS-CoV-2 cell invasion, preventing attachment and/or entry of the virus. To this aim, we search for possible interactions lactoferrin may have with virus structural proteins and host receptors. Representing the molecular iso-electron surface of proteins in terms of 2D-Zernike descriptors, we (i) identified putative regions on the lactoferrin surface able to bind sialic acid receptors on the host cell membrane, sheltering the cell from the virus attachment; (ii) showed that no significant shape complementarity is present between lactoferrin and the ACE2 receptor, while (iii) two high complementarity regions are found on the N- and C-terminal domains of the SARS-CoV-2 spike protein, hinting at a possible competition between lactoferrin and ACE2 for the binding to the spike protein.
Competing endogenous RNA crosstalk at system level
2019
PLoS Computational Biology
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microRNAs (miRNAs) regulate gene expression at post-transcriptional level by repressing target RNA molecules. Competition to bind miRNAs tends in turn to correlate their targets, establishing effective RNA-RNA interactions that can influence expression levels, buffer fluctuations and promote signal propagation. Such a potential has been characterized mathematically for small motifs both at steady state and away from stationarity. Experimental evidence, on the other hand, suggests that competing
doi:10.1371/journal.pcbi.1007474
pmid:31675359
pmcid:PMC6853376
fatcat:3kqgrmifing5zhijqymakrdg6u
more »
... endogenous RNA (ceRNA) crosstalk is rather weak. Extended miRNA-RNA networks could however favour the integration of many crosstalk interactions, leading to significant large-scale effects in spite of the weakness of individual links. To clarify the extent to which crosstalk is sustained by the miRNA interactome, we have studied its emergent systemic features in silico in large-scale miRNA-RNA network reconstructions. We show that, although generically weak, system-level crosstalk patterns (i) are enhanced by transcriptional heterogeneities, (ii) can achieve high-intensity even for RNAs that are not co-regulated, (iii) are robust to variability in transcription rates, and (iv) are significantly non-local, i.e. correlate weakly with miRNA-RNA interaction parameters. Furthermore, RNA levels are generically more stable when crosstalk is strongest. As some of these features appear to be encoded in the network's topology, crosstalk may functionally be favoured by natural selection. These results suggest that, besides their repressive role, miRNAs mediate a weak but resilient and context-independent network of cross-regulatory interactions that interconnect the transcriptome, stabilize expression levels and support system-level responses.
New algorithm to determine a minimal representation of the molecular surface
[article]
2021
arXiv
pre-print
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Most proteins perform their biological function by interacting with one or more molecular partners. In this respect, characterizing the features of the molecular surface, especially in the portions where the interaction takes place, turned out to be a crucial step in the investigation of the mechanisms of recognition and binding between molecules. Predictive methods often rely on extensive samplings of molecular patches with the aim to identify hot spots on the surface. In this framework,
arXiv:2107.07954v1
fatcat:uzzunfwndvedbhmm7wmsvp2vdi
more »
... is of large proteins and/or many molecular dynamics frames is often unfeasible due to the high computational cost. Thus, finding optimal ways to reduce the number of points to be sampled maintaining the biological information carried by the molecular surface is pivotal. Here, we present a new theoretical and computational algorithm with the aim of determining a subset of surface points, appropriately selected in space, in order to maximize the information of the overall shape of the molecule by minimizing the number of total points. We test our procedure by looking at the local shape of the surface through a recently developed method based on the formalism of Zernike polynomials in two dimensions, which is able to characterize the local shape properties of portions of molecular surfaces. The results of this method show that a remarkably higher ability of this algorithm to reproduce the information of the complete molecular surface compared to uniform random sampling.
In-Silico evidence for two receptors based strategy of SARS-CoV-2
[article]
2020
bioRxiv
pre-print
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We propose a novel numerical method able to determine efficiently and effectively the relationship of complementarity between portions of proteins surfaces. This innovative and general procedure, based on the representation of the molecular iso-electron density surface in terms of 2D Zernike polynomials, allows the rapid and quantitative assessment of the geometrical shape complementarity between interacting proteins, that was unfeasible with previous methods. We first tested the method with a
doi:10.1101/2020.03.24.006197
fatcat:gxdoejyxxbbc3ovglb5f2iqxmq
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... arge dataset of known protein complexes obtaining an overall area under the ROC curve of 0.69 in the blind recognition of binding sites and then applied it to investigate the features of the interaction between the Spike protein of SARS-Cov-2 and human cellular receptors. Our results indicate that SARS-CoV-2 uses a dual strategy: its spike protein could also interact with sialic acid receptors of the cells in the upper airways, in addition to the known interaction with Angiotensin-converting enzyme 2.
Thermometer: a webserver to predict protein thermal stability
2022
Bioinformatics
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.; Miotto et al.) . ...
We obtained 15 additional protein structures to be added to the dataset proposed in Miotto et al., 2018. ...
doi:10.1093/bioinformatics/btab868
pmid:35020787
pmcid:PMC8963285
fatcat:fj2pu3nmpvh5lf4dcrdka662fe
Does blood type affect the COVID-19 infection pattern?
2021
PLoS ONE
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Visualization: Mattia Miotto, Giorgio Gosti. Writing -original draft: Mattia Miotto, Lorenzo Di Rienzo, Giorgio Gosti, Edoardo Milanetti, Giancarlo Ruocco. ...
Writing -review & editing: Mattia Miotto, Lorenzo Di Rienzo, Giorgio Gosti, Edoardo Milanetti, Giancarlo Ruocco. ...
doi:10.1371/journal.pone.0251535
pmid:33984040
fatcat:a7nzrp64yfdavdh44eah34pppa
Investigating the side-chain structural organization behind the stability of protein folding and binding
[article]
2021
arXiv
pre-print
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What are the molecular mechanisms that dictate protein-protein binding stability and whether those are related to the ones behind protein fold stability are still largely open questions. Indeed, despite many past efforts, we still lack definitive models to account for experimental quantities like protein melting temperature or complex binding affinity. Here, we investigate and compare chemical and physical features on a dataset of protein with known melting temperature as well as a large
arXiv:2107.08099v1
fatcat:y3233a47pbgkrjvsr6uoe47snu
more »
... of protein-protein complexes with reliable experimental binding affinity. In particular, we probed the aminoacid composition and the organization of the network of intramolecular and intermolecular interaction energies among residues. We found that hydrophobic residues present on the protein surfaces are preferentially located in the binding regions, while charged residues behave oppositely. In addition, the abundance of polar amino acid like Serine and Proline correlates with the binding affinity of the complexes. Analysing the interaction energies we found that distant Coulombic interactions are responsible for thermal stability while the total inter-molecular van der Waals energy correlates with protein-protein binding affinity.
Does blood type affect the COVID-19 infection pattern?
[article]
2020
arXiv
pre-print
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Among the many aspects that characterize the COVID-19 pandemic, two seem particularly challenging to understand: (i) the great geographical differences in the degree of virus contagiousness and lethality which were found in the different phases of the epidemic progression, and (ii) the potential role of the infected people's blood type in both the virus infectivity and the progression of the disease. A recent hypothesis could shed some light on both aspects. Specifically, it has been proposed
arXiv:2007.06296v2
fatcat:2vprokijizaedjgpcqm2sf47xy
more »
... at in the subject-to-subject transfer SARS-CoV-2 conserves on its capsid the erythrocytes' antigens of the source subject. Thus these conserved antigens can potentially cause an immune reaction in a receiving subject that has previously acquired specific antibodies for the source subject antigens. This hypothesis implies a blood type-dependent infection rate. The strong geographical dependence of the blood type distribution could be, therefore, one of the factors at the origin of the observed heterogeneity in the epidemics spread. Here, we present an epidemiological deterministic model where the infection rules based on blood types are taken into account and compare our model outcomes with the exiting worldwide infection progression data. We found an overall good agreement, which strengthens the hypothesis that blood types do play a role in the COVID-19 infection.
Insights on protein thermal stability: a graph representation of molecular interactions
[article]
2018
biorxiv/medrxiv
pre-print
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Understanding the molecular mechanisms of protein thermal stability is an important challenge in modern biology. Indeed, knowing the temperature at which proteins are stable has important theoretical implications, that are intimately linked with properties of the native fold, and a wide range of potential applications from drug design to the optimization of enzyme activity. Here, we present a novel graph-theoretical framework to assess thermal stability based on the protein structure without
doi:10.1101/354266
fatcat:ag6xyow36zc57lwy533xauhqwi
more »
... a priori information. We describe proteins as energy-weighted inter- action networks and compare them with ensembles of interaction networks. We investigated how evolution shapes the position of specific interactions within the 3D native structure. We present a parameter-free network descriptor that permits to distinguish thermostable and mesostable proteins with an accuracy of 76% and Area Under the Roc Curve of 78%.
Molecular Mechanisms Behind Anti SARS-CoV-2 Action of Lactoferrin
2021
Frontiers in Molecular Biosciences
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Frontiers in Molecular Biosciences | www.frontiersin.org February 2021 | Volume 8 | Article 607443
Miotto et al.Anti SARS-CoV-2 Action of Lactoferrin ...
surface of cellular constituents, like membrane proteins Varki (2016) and are involved in many cell functions like support, signaling, protein folding, and protection Bishop and Gagneux (2007) and Miotto ...
doi:10.3389/fmolb.2021.607443
pmid:33659275
pmcid:PMC7917183
fatcat:yd4tiyh36jh2hhxqir2yjxznem
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