Adaptive Mechanism Research Articles

Clinical homologous recombination repair gene reversion analysis identifies mechanisms of resistance to PARP inhibitors and platinum‐chemotherapy

AbstractIdentifying mechanisms underlying cancer resistance to therapy is vital for advancing treatment strategies. Pathogenic mutations of homologous recombination repair (HRR) genes are known biomarkers for platinum (Pt)‐based chemotherapy and poly ADP ribose polymerase inhibitors (PARPi) effectiveness. Yet, the dynamics of HRR reversion mutations, which may herald therapy resistance, are not fully elucidated. Addressing this gap, our study analyzed secondary HRR gene mutations in a comprehensive pan‐cancer data set of approximately 13,000 patients who underwent targeted next‐generation sequencing. We identified a subset of patients harboring secondary mutations, which were further categorized into three tiers based on their nature, and occur in the presence of a primary pathogenic mutation, notably in BRCA1, BRCA2, PALB2, and RAD51D genes. Here we show that secondary BRCA2 mutations, indicative of adaptive resistance, emerge post‐Pt/Olaparib treatment. This challenges the prevailing notion that pathogenic HRR mutations uniformly predict therapeutic sensitivity, highlighting a nuanced genetic interplay that impacts treatment success. This investigation enriches our understanding of cancer's adaptive mechanisms against therapy, suggesting a pivotal shift towards more personalized, dynamic treatment strategies. It underscores the imperative of adapting to cancer's genetic evolution, aiming for a step ahead in the ongoing battle against this disease.

Feedback of chain elongation microorganisms on iron-based conductive materials: Enhanced microbial functions and biotoxicity adaptation mechanisms

Despite the increased research efforts aimed at understanding iron-based conductive materials (CMs) for facilitating chain elongation (CE) to produce medium chain fatty acids (MCFAs), the impact of these materials on microbial community functions and the adaptation mechanisms to their biotoxicity remain unclear. This study found that the supply of zero-valent iron (ZVI) and magnetite enhanced the MCFAs carbon-flow distribution by 26 % and 52 %, respectively. Metagenomic analysis revealed the upregulation of fatty acid metabolism, pyruvate metabolism and ABC transporters with ZVI and magnetite. The predominant functional microorganisms were Massilibacterium and Tidjanibacter with ZVI, and were Petrimonas and Candidatus_Microthrix with magnetite. Furthermore, it was demonstrated that CE microorganisms respond and adapt to the biotoxicity of iron-based CMs by adjusting Two-component system and Quorum sensing for the first time. In summary, this study provided a new deep-insight on the feedback mechanisms of CE microorganisms on iron-based CMs.

Adaptation to bioinvasions: When does it occur?

The presence of alien species represents a major cause of habitat degradation and biodiversity loss worldwide, constituting a critical environmental challenge of our time. Despite sometimes experiencing reduced propagule pressure, leading to a reduced genetic diversity and an increased chance of inbreeding depression, alien invaders are often able to thrive in the habitats of introduction, giving rise to the so-called "genetic paradox" of biological invasions. The adaptation of alien species to the new habitats is therefore a complex aspect of biological invasions, encompassing genetic, epigenetic, and ecological processes. Albeit numerous studies and reviews investigated the mechanistic foundation of the invaders' success, and aimed to solve the genetic paradox, still remains a crucial oversight regarding the temporal context in which adaptation takes place. Given the profound knowledge and management implications, this neglected aspect of invasion biology should receive more attention when examining invaders' ability to thrive in the habitats of introduction. Here, we discuss the adaptation mechanisms exhibited by alien species with the purpose of highlighting the timing of their occurrence during the invasion process. We analyze each stage of the invasion separately, providing evidence that adaptation mechanisms play a role in all of them. However, these mechanisms vary across the different stages of invasion, and are also influenced by other factors, such as the transport speed, the reproduction type of the invader, and the presence of human interventions. Finally, we provide insights into the implications for management, and identify knowledge gaps, suggesting avenues for future research that can shed light on species adaptability. This, in turn, will contribute to a more comprehensive understanding of biological invasions.

Cross-Border Water Management in Transboundary River conflicts in Palestine

Purpose: The aim of the study was to analyze cross-border water management in transboundary river conflicts in Palestine. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Research on cross-border water management in transboundary river conflicts stresses cooperation, trust-building, and integrated approaches for sustainable solutions. Equitable resource allocation, effective communication among riparian states, and international legal frameworks play vital roles in resolving disputes. Adaptive governance mechanisms are crucial for addressing changing hydrological conditions and political dynamics. Collaborative efforts are essential for managing transboundary river conflicts effectively. Unique Contribution to Theory, Practice and Policy: Hydro-hegemony theory, institutional collective action (ICA) theory & environmental peacebuilding theory may be used to anchor future studies on cross-border water management in transboundary river conflicts in Palestine. Implementing integrated water resources management (IWRM) approaches that involve stakeholders from all riparian countries can enhance practical efforts to address transboundary river conflicts. Developing robust legal and institutional frameworks at both national and international levels is crucial for resolving transboundary river conflicts and promoting cooperation.

A knowledge-enhanced interpretable network for early recurrence prediction of hepatocellular carcinoma via multi-phase CT imaging

BackgroundPredicting early recurrence (ER) of hepatocellular carcinoma (HCC) accurately can guide treatment decisions and further enhance survival. Computed tomography (CT) imaging, analyzed by deep learning (DL) models combining domain knowledge, has been employed for the prediction. However, these DL models utilized late fusion, restricting the interaction between domain knowledge and images during feature extraction, thereby limiting the prediction performance and compromising decision-making interpretability. MethodsWe propose a novel Vision Transformer (ViT)-based DL network, referred to as Dual-Style ViT (DSViT), to augment the interaction between domain knowledge and images and the effective fusion among multi-phase CT images for improving both predictive performance and interpretability. We apply the DSViT to develop pre-/post-operative models for predicting ER. Within DSViT, to balance the utilization between domain knowledge and images within DSViT, we propose an adaptive self-attention mechanism. Moreover, we present an attention-guided supervised learning module for balancing the contributions of multi-phase CT images to prediction and a domain knowledge self-supervision module for enhancing the fusion between domain knowledge and images, thereby further improving predictive performance. Finally, we provide the interpretability of the DSViT decision-making. ResultsExperiments on our multi-phase data demonstrate that DSViTs surpass the existing models across multiple performance metrics and provide the decision-making interpretability. Additional validation on a publicly available dataset underscores the generalizability of DSViT. ConclusionsThe proposed DSViT can significantly improve the performance and interpretability of ER prediction, thereby fortifying the trustworthiness of artificial intelligence tool for HCC ER prediction in clinical settings.

Metabolome and transcriptome reveal high abundance of bioactive substances in albino jujube fruit as potential function food

Little is known about the fruit quality of albino mutants, due to generally exhibited lethal phenotypes caused by restrained photosynthesis and energy metabolism. In this study, a non-lethal bud mutant of jujube that could bear fruit with higher nutrient content after leaf albinism was described. Compared to normal mature fruit, the albino fruit contained lower soluble sugar and titratable acid, as well as higher ascorbic acid, phenols and flavonoids contents. Through metabolome and transcriptome analyses, 109, 117, and 126 differentially accumulated metabolites (DAMs) and 1169, 797, and 3059 differentially expressed genes (DEGs) were identified in the young, white-ripened, and mature stages of albino and normal fruits, respectively. KEGG annotation indicated that DEGs and DAMs were mainly enriched in phenylpropanoid and flavonoid biosynthesis, glutathione metabolism, and α-linolenic acid metabolism. Moreover, ADH, GST17, and POD16 were identified as hub genes that play major roles in high abundance of chalcone, (−)-epigallocatechin, GSH, and total ascorbate. The alteration of bioactive substance content in albino fruits was an adaptive molecular mechanism that responded to adverse mutations, and reflected a higher antioxidant capacity. These findings provide new insights into bioactive compounds accumulation in albino mutants, and provide experimental evidence for albino fruit as a potential nutraceutical or functional food.

Distributed Adaptive Formation Tracking for a Class of Uncertain Nonlinear Multiagent Systems: Guaranteed Connectivity Under Moving Obstacles.

This article explores a guaranteed network connectivity problem during moving obstacle avoidance within a distributed formation tracking framework for uncertain nonlinear multiagent systems with range constraints. We investigate this problem based on a new adaptive distributed design using nonlinear errors and auxiliary signals. Within the detection range, each agent regards other agents and static or dynamic objects as obstacles. The nonlinear error variables for formation tracking and collision avoidance are presented, and the auxiliary signals in formation tracking errors are introduced to maintain network connectivity under the avoidance mechanism. The adaptive formation controllers using command-filtered backstepping are constructed to ensure closed-loop stability with collision avoidance and preserved connectivity. Compared with the previous formation results, the resulting features are as follows: 1) the nonlinear error function for the avoidance mechanism is considered an error variable, and an adaptive tuning mechanism for estimating the dynamic obstacle velocity is derived in a Lyapunov-based control design procedure; 2) network connectivity during dynamic obstacle avoidance is preserved by constructing the auxiliary signals; and 3) owing to neural networks-based compensating variables, the bounding conditions of time derivatives of virtual controllers are not required in the stability analysis.

Acute stress promotes effort mobilization for safety-related goals

Although the acute stress response is a highly adaptive survival mechanism, much remains unknown about how its activation impacts our decisions and actions. Based on its resource-mobilizing function, here we hypothesize that this intricate psychophysiological process may increase the willingness (motivation) to engage in effortful, energy-consuming, actions. Across two experiments (n = 80, n = 84), participants exposed to a validated stress-induction protocol, compared to a no-stress control condition, exhibited an increased willingness to exert physical effort (grip force) in the service of avoiding the possibility of experiencing aversive electrical stimulation (threat-of-shock), but not for the acquisition of rewards (money). Use of computational cognitive models linked this observation to subjective value computations that prioritize safety over the minimization of effort expenditure; especially when facing unlikely threats that can only be neutralized via high levels of grip force. Taken together, these results suggest that activation of the acute stress response can selectively alter the willingness to exert effort for safety-related goals. These findings are relevant for understanding how, under stress, we become motivated to engage in effortful actions aimed at avoiding aversive outcomes.

Communication-aware formation control for networks of AUVs

We propose a distributed formation control algorithm augmented with communication awareness. We consider autonomous underwater vehicles (AUVs) that are able to communicate over an acoustic link using a Time Division Multiple Access (TDMA) protocol, and to measure the Signal-to-Noise Ratio (SNR) of incoming messages. Based on the measured SNR and packet loss, we endow them with a distributed formation control scheme that accounts for the time-varying nature of the acoustic communication channel. This scheme allows a network of N AUVs to follow a pre-determined, twice-differentiable path while adapting their formation. The size of the formation is dynamically scaled by a formation adaptation mechanism to stabilize the estimated packet loss probability at a desired level. A distributed packet loss estimator is then built on top of the same average consensus routines used by the formation control algorithm, and thus comes with a minimal communication overhead. We test the algorithm by means of high-fidelity simulators, and verify its efficacy in making the network of agents retain formation-wide communication capabilities in a range of cases.

Beyond Homophily and Homogeneity Assumption: Relation-Based Frequency Adaptive Graph Neural Networks.

Graph neural networks (GNNs) have been playing important roles in various graph-related tasks. However, most existing GNNs are based on the assumption of homophily, so they cannot be directly generalized to heterophily settings where connected nodes may have different features and class labels. Moreover, real-world graphs often arise from highly entangled latent factors, but the existing GNNs tend to ignore this and simply denote the heterogeneous relations between nodes as binary-valued homogeneous edges. In this article, we propose a novel relation-based frequency adaptive GNN (RFA-GNN) to handle both heterophily and heterogeneity in a unified framework. RFA-GNN first decomposes an input graph into multiple relation graphs, each representing a latent relation. More importantly, we provide detailed theoretical analysis from the perspective of spectral signal processing. Based on this, we propose a relation-based frequency adaptive mechanism that adaptively picks up signals of different frequencies in each corresponding relation space in the message-passing process. Extensive experiments on synthetic and real-world datasets show qualitatively and quantitatively that RFA-GNN yields truly encouraging results for both the heterophily and heterogeneity settings. Codes are publicly available at: https://github.com/LirongWu/RFA-GNN.

Error-based Implicit Learning in Language: The Effect of Sentence Context and Constraint in a Repetition Paradigm.

Prediction errors drive implicit learning in language, but the specific mechanisms underlying these effects remain debated. This issue was addressed in an EEG study manipulating the context of a repeated unpredictable word (repetition of the complete sentence or repetition of the word in a new sentence context) and sentence constraint. For the manipulation of sentence constraint, unexpected words were presented either in high-constraint (eliciting a precise prediction) or low-constraint sentences (not eliciting any specific prediction). Repetition-induced reduction of N400 amplitudes and of power in the alpha/beta frequency band was larger for words repeated with their sentence context as compared with words repeated in a new low-constraint context, suggesting that implicit learning happens not only at the level of individual items but additionally improves sentence-based predictions. These processing benefits for repeated sentences did not differ between constraint conditions, suggesting that sentence-based prediction update might be proportional to the amount of unpredicted semantic information, rather than to the precision of the prediction that was violated. In addition, the consequences of high-constraint prediction violations, as reflected in a frontal positivity and increased theta band power, were reduced with repetition. Overall, our findings suggest a powerful and specific adaptation mechanism that allows the language system to quickly adapt its predictions when unexpected semantic information is processed, irrespective of sentence constraint, and to reduce potential costs of strong predictions that were violated.

The shaping of mRNA translation plasticity by RNA G-quadruplexes in cancer progression and therapy resistance.

Translational reprogramming in response to oncogenic signaling or microenvironmental stress factors shapes the proteome of cancer cells, enabling adaptation and phenotypic changes underlying cell plasticity, tumor progression and response to cancer therapy. Among the mechanisms regulating translation are RNA G-quadruplexes (RG4s), non-canonical four-stranded structures whose conformational modulation by small molecule ligands and RNA-binding proteins affects the expression of cancer proteins. Here, we discuss the role of RG4s in the regulation of mRNA translation by focusing on paradigmatic examples showing their contribution to adaptive mechanisms of mRNA translation in cancer.

Periostin regulates lysyl oxidase through ERK1/2 MAPK-dependent serum response factor in activated cardiac fibroblasts.

Collagen crosslinking, mediated by lysyl oxidase, is an adaptive mechanism of the cardiac repair process initiated by cardiac fibroblasts postmyocardial injury. However, excessive crosslinking leads to cardiac wall stiffening, which impairs the contractile properties of the left ventricle and leads to heart failure. In this study, we investigated the role of periostin, a matricellular protein, in the regulation of lysyl oxidase in cardiac fibroblasts in response to angiotensin II and TGFβ1. Our results indicated that periostin silencing abolished the angiotensin II and TGFβ1-mediated upregulation of lysyl oxidase. Furthermore, the attenuation of periostin expression resulted in a notable reduction in the activity of lysyl oxidase. Downstream of periostin, ERK1/2 MAPK signaling was found to be activated, which in turn transcriptionally upregulates the serum response factor to facilitate the enhanced expression of lysyl oxidase. The periostin-lysyl oxidase association was also positively correlated in an in vivo rat model of myocardial infarction. The expression of periostin and lysyl oxidase was upregulated in the collagen-rich fibrotic scar tissue of the left ventricle. Remarkably, echocardiography data showed a reduction in the left ventricular wall movement, ejection fraction, and fractional shortening, indicative of enhanced stiffening of the cardiac wall. These findings shed light on the mechanistic role of periostin in the collagen crosslinking initiated by activated cardiac fibroblasts. Our findings signify periostin as a possible therapeutic target to reduce excessive collagen crosslinking that contributes to the structural remodeling associated with heart failure.

Optimal Prescription for Superior Outcomes: A Comparative Analysis of Inter-Individual Variability in Adaptations to Small-Sided Games and Short Sprint Interval Training in Young Basketball Players.

This study compared the inter-individual variability in adaptive responses to six weeks of small-sided games (SSG) and short sprint interval training (sSIT) in young basketball players. Thirty well-trained young athletes (age: 16.4 ± 0.6 years; stature: 190 ± 8.4 cm; weight: 84.1 ± 8.2 kg) voluntarily participated and were randomly assigned to SSG (3 sets of 5 min 3v3 on full length (28 m) and half-width (7.5 m) court, with 2 minutes of passive recovery in-between), sSIT (3 sets of 12 × 5 s sprinting with 20 s recovery between efforts and 2 min of rest between sets), or CON (routine basketball-specific technical and tactical drills) groups, each of ten. Before and after the training period, participants underwent a series of laboratory- and field-based measurements to evaluate their maximum oxygen uptake (V̇O2max), first and second ventilatory threshold (VT1 and VT2), oxygen pulse, peak and average power output (PPO and APO), linear speed, change of direction (COD), countermovement jump (CMJ), and vertical jump (VJ). Both SSG and sSIT sufficiently stimulated adaptive mechanisms involved in enhancement of the mentioned variables (p < 0.05). However, sSIT resulted in lower residuals in percent changes in V̇O2max (p = 0.02), O2pulse (p = 0.005), VT1 (p = 0.001), PPO (p = 0.03), and linear speed (p = 0.01) across athletes compared to the SSG. Moreover, sSIT resulted in more responders than SSG in V̇O2max (p = 0.02, φ = 0.500), O2pulse (p = 0.003, φ = 0.655), VT1 (p = 0.003, φ = 0.655), VT2 (p = 0.05, φ = 0.436), and linear speed (p = 0.05, φ = 0.420). Our results indicate that sSIT creates a more consistent level of mechanical and physiological stimulus than SSG, potentially leading to more similar adaptations across team members.

The systematic codon usage bias has an important effect on genetic adaption in native species

Random mutations increase genetic variety and natural selection enhances adaption over generations. Codon usage biases (CUB) provide clues about the genome adaptation mechanisms of native species and extremophile species. Significant numbers of gene (CDS) of nine classes of endangered, native species, including extremophiles and mesophiles were utilised to compute CUB. Codon usage patterns differ among the lineages of endangered and extremophiles with native species. Polymorphic usage of nucleotides with codon burial suggests parallelism of native species within relatively confined taxonomic groups. Utilizing the deviation pattern of CUB of endangered and native species, I present a calculation parameter to estimate the extinction risk of endangered species. Species diversity and extinction risk are both positively associated with the propensity of random mutation in CDS (Coding DNA sequence). Codon bias tenet profoundly selected and it governs to adaptive evolution of native species.

A hierarchical adaptive selection neural network for dynamic impact localization of wind turbine blades

This paper focuses on the localization problem of dynamic impacts that can lead to significant damages on wind turbine blades (WTBs). Localization of dynamic impacts on WTBs is essential for wind turbines due to their vulnerability to dynamic impacts such as birds, stones, hails. The proposed deep learning methodology contributes to accurately locate the impacted blade and specific position using the measurements from a limited number of sensors. In particular, a novel hierarchical adaptive selection neural network is proposed, which integrates a classification subnetwork and a regression subnetwork. Specifically, an adaptive blade selection mechanism is designed to determine the impacted blade for classification while an adaptive window selection mechanism is developed to highlight the representative time period for regression. By deploying a limited number of sensors to acquire measured vibration data, the proposed method can accurately identify the collision locations of transient impacts loaded on WTBs. In both simulated and real-world experiments, the proposed method achieves the mean absolute error of 0.189 centimeter and 1.088 centimeter for impact localization. The experimental results demonstrate the superior performance of the proposed model in comparison with the existing methods for localizing impulsive loads on WTBs.

Exploring the dynamic adaptive responses of Epimedium pubescens to phosphorus deficiency by Integrated transcriptome and miRNA analysis

Phosphorus, a crucial macronutrient essential for plant growth and development. Due to widespread phosphorus deficiency in soils, phosphorus deficiency stress has become one of the major abiotic stresses that plants encounter. Despite the evolution of adaptive mechanisms in plants to address phosphorus deficiency, the specific strategies employed by species such as Epimedium pubescens remain elusive. Therefore, this study observed the changes in the growth, physiological reponses, and active components accumulation in E. pubescensunder phosphorus deficiency treatment, and integrated transcriptome and miRNA analysis, so as to offer comprehensive insights into the adaptive mechanisms employed by E. pubescens in response to phosphorus deficiency across various stages of phosphorus treatment. Remarkably, our findings indicate that phosphorus deficiency induces root growth stimulation in E. pubescens, while concurrently inhibiting the growth of leaves, which are of medicinal value. Surprisingly, this stressful condition results in an augmented accumulation of active components in the leaves. During the early stages (30 days), leaves respond by upregulating genes associated with carbon metabolism, flavonoid biosynthesis, and hormone signaling. This adaptive response facilitates energy production, ROS scavenging, and morphological adjustments to cope with short-term phosphorus deficiency and sustain its growth. As time progresses (90 days), the expression of genes related to phosphorus cycling and recycling in leaves is upregulated, and transcriptional and post-transcriptional regulation (miRNA regulation and protein modification) is enhanced. Simultaneously, plant growth is further suppressed, and it gradually begins to discard and decompose leaves to resist the challenges of long-term phosphorus deficiency stress and sustain survival. In conclusion, our study deeply and comprehensively reveals adaptive strategies utilized by E. pubescens in response to phosphorus deficiency, demonstrating its resilience and thriving potential under stressful conditions. Furthermore, it provides valuable information on potential target genes for the cultivation of E. pubescens genotypes tolerant to low phosphorus.

Sex-dependent intra-islet structural rearrangements affecting alpha-to-beta cell interactions lead to adaptive enhancements of Ca2+ dynamics in prediabetic beta cells.

Prediabetic pancreatic beta cells can adapt their function to maintain normoglycaemia for a limited period of time, after which diabetes mellitus will manifest upon beta cell exhaustion. Understanding sex-specific beta cell compensatory mechanisms and their failure in prediabetes (impaired glucose tolerance) is crucial for early disease diagnosis and individualised treatment. Our aims were as follows: (1) to determine the key time points of the progression from beta cells' functional adaptations to their failure in vivo; and (2) to mechanistically explain in vivo sex-specific beta cell compensatory mechanisms and their failure in prediabetes. Islets from male and female transgenic Ins1CreERT2-GCaMP3 mice were transplanted into the anterior chamber of the eye of 10- to 12-week-old sex-matched C57BL/6J mice. Recipient mice were fed either a control diet (CD) or western diet (WD) for a maximum of 4 months. Metabolic variables were evaluated monthly. Beta cell cytoplasmic free calcium concentration ([Ca2+]i) dynamics were monitored in vivo longitudinally by image fluorescence of the GCaMP3 reporter islets. Global islet beta cell [Ca2+]i dynamics in line with single beta cell [Ca2+]i analysis were used for beta cell coordination studies. The glucagon receptor antagonist L-168,049 (4 mmol/l) was applied topically to the transplanted eyes to evaluate in vivo the effect of glucagon on beta cell [Ca2+]idynamics. Human islets from non-diabetic women and men were cultured for 24 h in either a control medium or high-fat/high-glucose medium in the presence or absence of the glucagon receptor antagonist L-168,049. [Ca2+]i dynamics of human islets were evaluated in vitro after 1 h exposure to Fura-10. Mice fed a WD for 1 month displayed increased beta cell [Ca2+]i dynamics linked to enhanced insulin secretion as a functional compensatory mechanism in prediabetes. Recruitment of inactive beta cells in WD-fed mice explained the improved beta cell function adaptation observed in vivo; this occurred in a sex-specific manner. Mechanistically, this was attributable to an intra-islet structural rearrangement involving alpha cells. These sex-dependent cytoarchitecture reorganisations, observed in both mice and humans, induced enhanced paracrine input from adjacent alpha cells, adjusting the glucose setpoint and amplifying the insulin secretion pathway. When WD feeding was prolonged, female mice maintained the adaptive mechanism due to their intrinsically high proportion of alpha cells. In males, [Ca2+]i dynamics progressively declined subsequent to glucose stimulation while insulin secretion continue to increase, suggesting uncoordinated beta cell function as an early sign of diabetes. We identified increased coordination of [Ca2+]i dynamics as a beta cell functional adaptation mechanisms in prediabetes. Importantly, we uncovered the mechanisms by which sex-dependent beta cell [Ca2+]i dynamics coordination is orchestrated by an intra-islet structure reorganisation increasing the paracrine input from alpha cells on beta cell function. Moreover, we identified reduced [Ca2+]i dynamics coordination in response to glucose as an early sign of diabetes preceding beta cell secretory dysfunction, with males being more vulnerable. Alterations in coordination capacity of [Ca2+]i dynamics may thus serve as an early marker for beta cell failure in prediabetes.

The phage shock protein (PSP) envelope stress response: discovery of novel partners and evolutionary history.

Bacterial phage shock protein (PSP) systems stabilize the bacterial cell membrane and protect against envelope stress. These systems have been associated with virulence, but despite their critical roles, PSP components are not well characterized outside proteobacteria. Using comparative genomics and protein sequence-structure-function analyses, we systematically identified and analyzed PSP homologs, phyletic patterns, domain architectures, and gene neighborhoods. This approach underscored the evolutionary significance of the system, revealing that its core protein PspA (Snf7 in ESCRT outside bacteria) was present in the last universal common ancestor and that this ancestral functionality has since diversified into multiple novel, distinct PSP systems across life. Several novel partners of the PSP system were identified: (i) the Toastrack domain, likely facilitating assembly of sub-membrane stress-sensing and signaling complexes, (ii) the newly defined HTH-associated α-helical signaling domain-PadR-like transcriptional regulator pair system, and (iii) multiple independent associations with ATPase, CesT/Tir-like chaperone, and Band-7 domains in proteins thought to mediate sub-membrane dynamics. Our work also uncovered links between the PSP components and other domains, such as novel variants of SHOCT-like domains, suggesting roles in assembling membrane-associated complexes of proteins with disparate biochemical functions. Results are available at our interactive web app, https://jravilab.org/psp.IMPORTANCEPhage shock proteins (PSP) are virulence-associated, cell membrane stress-protective systems. They have mostly been characterized in Proteobacteria and Firmicutes. We now show that a minimal PSP system was present in the last universal common ancestor that evolved and diversified into newly identified functional contexts. Recognizing the conservation and evolution of PSP systems across bacterial phyla contributes to our understanding of stress response mechanisms in prokaryotes. Moreover, the newly discovered PSP modularity will likely prompt new studies of lineage-specific cell envelope structures, lifestyles, and adaptation mechanisms. Finally, our results validate the use of domain architecture and genetic context for discovery in comparative genomics.

An Adaptive Core-Nash Bargaining Game Consensus Mechanism for Group Decision Making

An Adaptive Core-Nash Bargaining Game Consensus Mechanism for Group Decision Making