Analysis and Prognosis of Failures in Intelligent Hybrid Systems Using Bioengineering: Gear Coupling

This work is of multidisciplinary concept, whose development is difficult to perform. Considering also that, in one of the steps, the similarity between the FRF of the vibration and acoustic signal is demonstrated. The objective of this work is the analysis and prognosis of the progression of failures of a pair of gears using the artificial immune system (AIS) of negative selection. In order to have this condition met, during the development of this work, the Wiener filter technique, the vibration and acoustic signal analysis (FRF), the application of negative selection AIS techniques for classification and grouping of signals were applied. The final result successfully demonstrates the effectiveness of the development process of this work and the robustness of the negative selection AIS algorithm.

Haplotype-based inference of the distribution of fitness effects

Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.

SARS-CoV-2 comes up with a perfect recipe for disaster: Each mutation plays a specific role in the evolution of variants of concern

COVID-19 pandemic has extended for close to two years with the continuous emergence of new variants. Mutations in the receptor binding domain (RBD) are of prime importance in dictating the SARS-CoV-2 spike protein function. By studying a series of single, double and triple RBD mutants, we have delineated the individual and collective effects of RBD mutations in a variant of concern (VOC) containing multiple mutations (Gamma variant; K417T/E484K/N501Y) on binding to angiotensin converting enzyme 2 (ACE2) receptor, antibody escape and protein stability. Our results show that each mutation in the VOC serves a distinct function that improves virus fitness landscape supporting its positive selection, even though individual mutations have deleterious effects that make them prone to negative selection. K417T contributes to increased expression, increased stability and escape from class 1 antibodies; however, it has decreased ACE2 binding. E484K contributes to escape from class 2 antibodies; however, it has decreased expression, decreased stability, and decreased ACE2 binding affinity. N501Y increases receptor binding affinity; however, it has decreased stability and decreased expression. But when these mutations come together, the deleterious effects are mitigated in the triple mutant due to the presence of compensatory effects, which improves the chances of selection of mutations together. These results show the implications of presence of multiple mutations on virus evolution and indicate the emergence of future SARS-CoV-2 variants with multiple mutations that enhance viral fitness on different fronts by balancing both positive and negative selection.

Regulation of positive and negative selection and TCR signaling during thymic T cell development by capicua

Central tolerance is achieved through positive and negative selection of thymocytes mediated by T cell receptor (TCR) signaling strength. Thus, dysregulation of the thymic selection process often leads to autoimmunity. Here, we show that Capicua (CIC), a transcriptional repressor that suppresses autoimmunity, controls the thymic selection process. Loss of CIC prior to T-cell lineage commitment impairs both positive and negative selection of thymocytes. CIC deficiency attenuated TCR signaling in CD4+CD8+ double-positive (DP) cells, as evidenced by a decrease in CD5 and phospho-ERK levels and calcium flux. We identified Spry4, Dusp4, Dusp6, and Spred1 as CIC target genes that could inhibit TCR signaling in DP cells. Furthermore, impaired positive selection and TCR signaling were partially rescued in Cic and Spry4 double mutant mice. Our findings indicate that CIC is a transcription factor required for thymic T cell development and suggests that CIC acts at multiple stages of T cell development and differentiation to prevent autoimmunity.

MONITORAMENTO DE FALHAS EM SISTEMAS DINÂMICOS UTILIZANDO UM MÉTODO DE ANÁLISE DE DADOS BASEADO NO ALGORITMO DE SELEÇÃO NEGATIVA

This work presents the application of a method for monitoring and diagnosing failures in mechanical structures based on the theory of vibration signals and on Artificial Immune Systems to assist in data processing. It uses the Negative Selection Algorithm as a tool to identify fault samples extracted from the laboratory simulated signals of a dynamic rotor. This methodology can help mechanical structure maintenance professionals, facilitating decision-making. The data set used in the processing of the intelligent system was generated through experiments. For normal (base-line) conditions, the signals of the rotor in free operation were used, that is, without the addition of unbalance mass, and for the fault conditions, unbalance masses were added to the system. The results are satisfactory, showing precision and robustness.

Investigating the evolvability of 'Escherichia coli nfsA' via simultaneous site-directed mutagenesis

<p>Bacterial nitroreductases are flavoenzymes able to catalyse the reduction of nitroaromatic compounds. The research presented in this thesis focused on NfsA_Ec, a nitroreductase from E. coli. NfsA_Ec is a promiscuous enzyme that can reduce a wide range of nitroaromatic antibiotics and prodrugs. This research sought to use NfsA_Ec as a model to improve our understanding of directed evolution, and also to identify NfsA_Ec variants exhibiting improved activation with a range of nil-bystander prodrugs for use in a targeted cell ablation system in zebrafish. There is a substantial gap between the levels of enzyme activity that nature can achieve and those that scientists can evolve in the lab. This suggests that conventional directed evolution techniques involving incremental improvements in enzyme activity may frequently fail to ascend even local fitness maxima. We sought to contrast such approaches with simultaneous site-directed mutagenesis, employing a library of 252 million unique nfsA variants. To determine whether two superior NfsA_Ec variants recovered from this library could have been identified using a conventional stepwise approach we generated all possible intermediates of these two enzyme variants and recreated the most logical evolutionary trajectory for each enzyme variant. This revealed that a stepwise mutagenesis approach could indeed have yielded both of these variants, but also that very few evolutionary trajectories were accessible due to complex epistatic interactions between substitutions in these enzymes. Moreover, many conventional stepwise mutagenesis approaches such as iterative saturation mutagenesis would have failed to identify key substitutions in these variants. We also investigated the “black-box” effect of directed evolution, using NfsA_Ec and a panel of nitroaromatic compounds to model the off-target effects an evolved enzyme can have within an existing metabolic network. We found that selection for improved niclosamide and chloramphenicol detoxification also improved activity with some structurally distinct prodrugs, but not others. Using a dual positive-negative selection, we recovered NfsA_Ec variants that were more specialised for their primary activities, however this came at a cost in terms of overall activity levels. The simultaneous site-directed nfsA_Ec mutagenesis library also had practical applications, enabling recovery of NfsA_Ec variants for targeted cell ablation in zebrafish models. These models involve the selective ablation of nitroreductase expressing cells without harming adjacent cells, to mimic a degenerative disease. Several NfsA_Ec variants were identified which were highly active with the nil-bystander prodrugs metronidazole, tinidazole, RB6145 and misonidazole when expressed in E. coli. However, these NfsA_Ec variants had inconsistent activities in our eukaryotic cell model (HEK-293). To expand the utility of the core ablation system, we sought to identify pairs of nitroreductases with non-overlapping prodrug specificities, suitable for use in a multiplex cell ablation system. Using a dual positive-negative selection, we recovered several NfsA_Ec variants that exhibited preferential nitrofurazone activation over metronidazole. Our lead variants for both applications are currently being trialed in zebrafish for their utility in generating degenerative disease models.</p>

Investigating the evolvability of 'Escherichia coli nfsA' via simultaneous site-directed mutagenesis

<p>Bacterial nitroreductases are flavoenzymes able to catalyse the reduction of nitroaromatic compounds. The research presented in this thesis focused on NfsA_Ec, a nitroreductase from E. coli. NfsA_Ec is a promiscuous enzyme that can reduce a wide range of nitroaromatic antibiotics and prodrugs. This research sought to use NfsA_Ec as a model to improve our understanding of directed evolution, and also to identify NfsA_Ec variants exhibiting improved activation with a range of nil-bystander prodrugs for use in a targeted cell ablation system in zebrafish. There is a substantial gap between the levels of enzyme activity that nature can achieve and those that scientists can evolve in the lab. This suggests that conventional directed evolution techniques involving incremental improvements in enzyme activity may frequently fail to ascend even local fitness maxima. We sought to contrast such approaches with simultaneous site-directed mutagenesis, employing a library of 252 million unique nfsA variants. To determine whether two superior NfsA_Ec variants recovered from this library could have been identified using a conventional stepwise approach we generated all possible intermediates of these two enzyme variants and recreated the most logical evolutionary trajectory for each enzyme variant. This revealed that a stepwise mutagenesis approach could indeed have yielded both of these variants, but also that very few evolutionary trajectories were accessible due to complex epistatic interactions between substitutions in these enzymes. Moreover, many conventional stepwise mutagenesis approaches such as iterative saturation mutagenesis would have failed to identify key substitutions in these variants. We also investigated the “black-box” effect of directed evolution, using NfsA_Ec and a panel of nitroaromatic compounds to model the off-target effects an evolved enzyme can have within an existing metabolic network. We found that selection for improved niclosamide and chloramphenicol detoxification also improved activity with some structurally distinct prodrugs, but not others. Using a dual positive-negative selection, we recovered NfsA_Ec variants that were more specialised for their primary activities, however this came at a cost in terms of overall activity levels. The simultaneous site-directed nfsA_Ec mutagenesis library also had practical applications, enabling recovery of NfsA_Ec variants for targeted cell ablation in zebrafish models. These models involve the selective ablation of nitroreductase expressing cells without harming adjacent cells, to mimic a degenerative disease. Several NfsA_Ec variants were identified which were highly active with the nil-bystander prodrugs metronidazole, tinidazole, RB6145 and misonidazole when expressed in E. coli. However, these NfsA_Ec variants had inconsistent activities in our eukaryotic cell model (HEK-293). To expand the utility of the core ablation system, we sought to identify pairs of nitroreductases with non-overlapping prodrug specificities, suitable for use in a multiplex cell ablation system. Using a dual positive-negative selection, we recovered several NfsA_Ec variants that exhibited preferential nitrofurazone activation over metronidazole. Our lead variants for both applications are currently being trialed in zebrafish for their utility in generating degenerative disease models.</p>

Interpreting dN/dS under different selective regimes in cancer evolution

The standard relationship between the dN/dS statistic and the selection coefficient is contingent upon the computation of the rate of fixation of non-synonymous and synonymous mutations among divergent lineages (substitutions). In cancer genomics, however, dN/dS is typically calculated by including mutations that are still segregating in the cell population. The interpretation of dN/dS within sexual populations has been shown to be problematic. Here we used a simple model of somatic evolution to study the relationship between dN/dS and the selection coefficient in the presence of deleterious, neutral, and beneficial mutations in cancer. We found that dN/dS can be used to distinguish cancer genes under positive or negative selection, but it is not always informative about the magnitude of the selection coefficient. In particular, under the asexual scenario simulated, dN/dS is insensitive to negative selection strength. Furthermore, the relationship between dN/dS and the positive selection coefficient depends on the mutation detection threshold, and, in particular scenarios, it can become non-linear. Our results warn about the necessary caution when interpreting the results drawn from dN/dS estimates in cancer.

Evidence of positive and negative selection associated with DNA methylation

Signatures of negative selection are pervasive amongst complex traits and diseases. However, it is unclear whether such signatures exist for DNA methylation (DNAm) that has been proposed to have a functional role in disease. We estimate polygenicity, SNP-based heritability and model the joint distribution of effect size and minor allele frequency (MAF) to estimate a selection coefficient (S) for 2000 heritable DNAm sites in 1774 individuals from the Avon Longitudinal Study of Parents and Children. Additionally, we estimate S for meta stable epi alleles and DNAm sites associated with aging and mortality, birthweight and body mass index. Quantification of MAF-dependent genetic architectures estimated from genotype and DNAm reveal evidence of positive (S>0) and negative selection (S<0) and confirm previous evidence of negative selection for birthweight. Evidence of both negative and positive selection highlights the role of DNAm as an intermediary in multiple biological pathways with competing function.