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Antimicrobial peptides (AMPs) are molecules found in most organisms, playing a vital role in innate immune defense against pathogens. Their mechanism of action involves the disruption of bacterial cell membranes, causing leakage of cellular contents and ultimately leading to cell death. While AMPs typically lack a defined structure in solution, they often assume a defined conformation when interacting with bacterial membranes. Given this structural flexibility, we investigated whether intrinsically disordered regions (IDRs) with AMP-like properties could exhibit antimicrobial activity. We tested 14 peptides from different IDRs predicted to have antimicrobial activity and found that nearly all of them did not display the anticipated effects. These peptides failed to adopt a defined secondary structure and had compromised membrane interactions, resulting in a lack of antimicrobial activity. We hypothesize that evolutionary constraints may prevent IDRs from folding, even in membrane-like environments, limiting their antimicrobial potential. Moreover, our research reveals that current antimicrobial predictors fail to accurately capture the structural features of peptides when dealing with intrinsically unstructured sequences. Hence, the results presented here may have far-reaching implications for designing and improving antimicrobial strategies and therapies against infectious diseases.

ABSTRACT The alarming rise of antibiotic-resistant bacterial infections is driving efforts to develop alternatives to conventional antibiotics. In this context, antimicrobial peptides (AMPs) have emerged as promising candidates for their ability to target a broad range of microorganisms. However, the development of AMPs with optimal potency, selectivity, and/or stability profiles remains a challenge. To address it, computational tools for predicting AMP properties and designing novel peptides have gained increasing attention. PyAMPA is a novel platform for AMP discovery. It consists of five modules, namely AMPScreen, AMPValidate, AMPSolve, AMPMutate, and AMPOptimize, that allow high-throughput proteome inspection, candidate screening, and optimization through point-mutation and genetic algorithms. The platform also offers additional tools for predicting and evaluating AMP properties, including antimicrobial and cytotoxic activity, and peptide half-life. By providing innovative and accessible inroads into AMP motifs in proteomes, PyAMPA will enable advances in AMP development and potential translation into clinically useful molecules. PyAMPA is available at: https://github.com/SysBioUAB/PyAMPAIMPORTANCEThis paper introduces PyAMPA, a new bioinformatics platform designed for the discovery and optimization of antimicrobial peptides (AMPs). It addresses the urgent need for new antimicrobials due to the rise of antibiotic-resistant infections. PyAMPA, with its five predictive modules -AMPScreen, AMPValidate, AMPSolve, AMPMutate and AMPOptimize, enables high-throughput screening of proteomes to identify potential AMP motifs and optimize them for clinical use. Its unique approach, combining prediction, design, and optimization tools, makes PyAMPA a robust solution for developing new AMP-based therapies, offering a significant advance in combatting antibiotic resistance.

The study of protein interactions in living organisms is fundamental for understanding biological processes and central metabolic pathways. Yet, our knowledge of the bacterial interactome remains limited. Here, we combined gene deletion mutant analysis with deep-learning protein folding using AlphaFold2 to predict the core bacterial essential interactome. We predicted and modeled 1402 interactions between essential proteins in bacteria and generated 146 high-accuracy models. Our analysis reveals previously unknown details about the assembly mechanisms of these complexes, highlighting the importance of specific structural features in their stability and function. Our work provides a framework for predicting the essential interactomes of bacteria and highlight the potential of deep-learning algorithms in advancing our understanding of the complex biology of living organisms. Also, the results presented here offer a promising approach to identify novel antibiotic targets.

Protein-protein interactions (PPIs) are involved in most cellular processes. Unfortunately, current knowledge of host-pathogen interactomes is still very limited. Experimental methods used to detect PPIs have several limitations, including increasing complexity and economic cost in large-scale screenings. Hence, computational methods are commonly used to support experimental data, although they generally suffer from high false-positive rates. To address this issue, we have created HPIPred, a host-pathogen PPI prediction tool based on numerical encoding of physicochemical properties. Unlike other available methods, HPIPred integrates phenotypic data to prioritize biologically meaningful results. We used HPIPred to screen the entire Homo sapiens and Pseudomonas aeruginosa PAO1 proteomes to generate a host-pathogen interactome with 763 interactions displaying a highly connected network topology. Our predictive model can be used to prioritize protein–protein interactions as potential targets for antibacterial drug development. Available at: https://github.com/SysBioUAB/hpi_predictor.

β-defensins are one of the most abundant and studied families of antimicrobial peptides (AMPs). Because of their selective toxicity to bacterial membranes and a broad spectrum of microbicidal action, β-defensins are regarded as potential therapeutic agents. This work focuses on a β-defensin-like AMP from the spiny lobster Panulirus argus (hereafter referred to as panusin or PaD). This AMP is structurally related to mammalian defensins via the presence of an αβ domain stabilized by disulfide bonds. Previous studies of PaD suggest that its C-terminus (Ct_PaD) contains the main structural determinants of antibacterial activity. To confirm this hypothesis, we made synthetic versions of PaD and Ct_PaD to determine the influence of the C-terminus on antimicrobial activity, cytotoxicity, proteolytic stability, and 3D structure. After successful solid-phase synthesis and folding, antibacterial assays of both peptides showed truncated Ct_PaD to be more active than native PaD, confirming the role of the C-terminus in activity and suggesting that cationic residues in that region enhance binding to negatively charged membranes. On the other hand, neither PaD nor Ct_PaD were hemolytic or cytotoxic in human cells. Proteolysis in human serum was also studied, showing high (>24 h) t1/2 values for PaD and lower but still considerable for Ct_PaD, indicating that the missing native disulfide bond in Ct_PaD alters protease resistance, albeit not decisively. NMR-2D experiments in water agree with the results obtained by circular dichroism (CD), where in SDS micelles, CD showed both peptides adopting an increasingly ordered structure in a hydrophobic environment, in tune with their ability to perturb bacterial membrane systems. In conclusion, while the β-defensin features of PaD are confirmed as advantageous in terms of antimicrobial activity, toxicity, and protease stability, the results of the present work suggest that these same features are preserved, even enhanced, in the structurally simpler Ct_PaD, which must therefore be viewed as a valuable lead for the development of novel anti-infectives.

Antimicrobial peptides (AMPs) are widely distributed molecules secreted mostly by cells of the innate immune system to prevent bacterial proliferation at the site of infection. As with classic antibiotics, continued treatment with AMPs can create resistance in bacteria. However, whether AMPs can generate tolerance as an intermediate stage towards resistance is not known. Here, we show that the treatment of Escherichia coli with different AMPs induces tolerance by lag, particularly for those peptides that have internal targets. This tolerance can be detected as different morphological and physiological changes, which depend on the type of peptide molecule the bacterium has been exposed to. In addition, we show that AMP tolerance can also affect antibiotic treatment. The genomic sequencing of AMP-tolerant strains shows that different mutations alter membrane composition, DNA replication, and translation. Some of these mutations have also been observed in antibiotic-resistant strains, suggesting that AMP tolerance could be a relevant step in the development of antibiotic resistance. Monitoring AMP tolerance is relevant vis-á-vis the eventual therapeutic use of AMPs and because cross-tolerance might favor the emergence of resistance against conventional antibiotic treatments.

Abstract Phase separation of soluble proteins into insoluble deposits is associated with numerous diseases. However, protein deposits can also function as membrane‐less compartments for many cellular processes. What are the fitness costs and benefits of forming such deposits in different conditions? Using a model protein that phase‐separates into deposits, we distinguish and quantify the fitness contribution due to the loss or gain of protein function and deposit formation in yeast. The environmental condition and the cellular demand for the protein function emerge as key determinants of fitness. Protein deposit formation can influence cell‐to‐cell variation in free protein abundance between individuals of a cell population (i.e., gene expression noise). This results in variable manifestation of protein function and a continuous range of phenotypes in a cell population, favoring survival of some individuals in certain environments. Thus, protein deposit formation by phase separation might be a mechanism to sense protein concentration in cells and to generate phenotypic variability. The selectable phenotypic variability, previously described for prions, could be a general property of proteins that can form phase‐separated assemblies and may influence cell fitness.

Ctn[15-34], the C-terminal section of crotalicidin (Ctn), a cathelicidin from a South American pit viper, is an antimicrobial and antitumoral peptide with remarkably longer stability in human serum than the parent Ctn. In this work, a set of topoisomers of both Ctn and Ctn[15-34], including the retro, enantio, and retroenantio versions, were synthesized and tested to investigate the structural requirements for activity. All topoisomers were as active as the cognate sequences against Gram-negative bacteria and tumor cells while slightly more toxic towards normal cells. More importantly, the enhanced serum stability of the D-amino-acid-containing versions suggests that such topoisomers must be preferentially considered as future antimicrobial and anticancer peptide leads.

Bacteria use protein-protein interactions to infect their hosts and hijack fundamental pathways, which ensures their survival and proliferation. Hence, the infectious capacity of the pathogen is closely related to its ability to interact with host proteins. Here, we show that hubs in the host-pathogen interactome are isolated in the pathogen network by adapting the geometry of the interacting interfaces. An imperfect mimicry of the eukaryotic interfaces allows pathogen proteins to actively bind to the host's target while preventing deleterious effects on the pathogen interactome. Understanding how bacteria recognize eukaryotic proteins may pave the way for the rational design of new antibiotic molecules.

Antimicrobial peptides (AMPs) are alternative therapeutics to traditional antibiotics against bacterial resistance. Our previous work identified an antimicrobial region at the N-terminus of the eosinophil cationic protein (ECP). Following structure-based analysis, a 30mer peptide (ECPep-L) was designed that combines antimicrobial action against Gram-negative species with lipopolysaccharides (LPS) binding and endotoxin-neutralization activities. Next, analogues that contain non-natural amino acids were designed to increase serum stability. Here, two analogues were selected for in vivo assays: the all-D version (ECPep-D) and the Arg to Orn version that incorporates a D-amino acid at position 2 (ECPep-2D-Orn). The peptide analogues retained high LPS-binding and anti-endotoxin activities. The peptides efficacy was tested in a murine acute infection model of Acinetobacter baumannii. Results highlighted a survival rate above 70% following a 3-day supervision with a single administration of ECPep-D. Moreover, in both ECPep-D and ECPep-2D-Orn peptide-treated groups, clinical symptoms improved significantly and the tissue infection was reduced to equivalent levels to mice treated with colistin, used as a last resort in the clinics. Moreover, treatment drastically reduced serum levels of TNF-α inflammation marker within the first 8 h. The present results support ECP-derived peptides as alternative candidates for the treatment of acute infections caused by Gram-negative bacteria.

Hubs tend to be essential for function in protein networks within organisms. Here, the authors show that during infection, it is the proteins with high centrality in theY. pestishost–pathogen interactome that are most important for pathogen fitness during infection, and highlight the importance of pathogen proteins that likely cause significant perturbation of the host interactome.

The rise in the number of antibiotic-resistant bacteria has become a serious threat to health, making it important to identify, characterize and optimize new molecules to help us to overcome the infections they cause. It is well known that Acinetobacter baumannii has a significant capacity to evade the actions of antibacterial drugs, leading to its emergence as one of the bacteria responsible for hospital and community-acquired infections. Nonetheless, how this pathogen infects and survives inside the host cell is unclear. In this study, we analyze the time-resolved transcriptional profile changes observed in human epithelial HeLa cells after infection by A. baumannii, demonstrating how it survives in host cells and starts to replicate 4 h post infection. These findings were achieved by sequencing RNA to obtain a set of Differentially Expressed Genes (DEGs) to understand how bacteria alter the host cells’ environment for their own benefit. We also determine common features observed in this set of genes and identify the protein–protein networks that reveal highly-interacted proteins. The combination of these findings paves the way for the discovery of new antimicrobial candidates for the treatment of multidrug-resistant bacteria.

Localized infections or disruption of the skin barrier can enable the entry of bacteria into the bloodstream, possibly leading to acute inflammation and sepsis. There is currently no holistic view on how bacteria can survive and spread in the bloodstream. In this context, we combined transposon mutagenesis, gene-expression profiling and a protein interaction network analysis to examine how uropathogenic Escherichia coli can proliferate in blood. Our results indicate that, upon migration from the urea to serum, E. coli reacts to the osmolarity difference, triggering a transcriptomic response in order to express survival genes. The proteins codified by these genes are precisely organized at the interactome level and specifically target short linear motifs located in disordered regions of host proteins. Such a coordinated response helps to explain how bacteria can adapt to and survive environmental changes within the host. Overall, our results provide a general framework for the study of bacteremia and reveal new targets for potential study as novel antimicrobials.

Here an inertial sensor-based monitoring system for measuring and analyzing upper limb movements is presented. The final goal is the integration of this motion-tracking device within a portable rehabilitation system for brain injury patients. A set of four inertial sensors mounted on a special garment worn by the patient provides the quaternions representing the patient upper limb’s orientation in space. A kinematic model is built to estimate 3D upper limb motion for accurate therapeutic evaluation. The human upper limb is represented as a kinematic chain of rigid bodies with three joints and six degrees of freedom. Validation of the system has been performed by co-registration of movements with a commercial optoelectronic tracking system. Successful results are shown that exhibit a high correlation among signals provided by both devices and obtained at the Institut Guttmann Neurorehabilitation Hospital.

Antimicrobial proteins and peptides (AMPs) are important effectors of the innate immune system that play a vital role in the prevention of infections. Recent advances have highlighted the similarity between AMPs and amyloid proteins. Using the Eosinophil Cationic Protein as a model, we have rationalized the structure-activity relationships between amyloid aggregation and antimicrobial activity. Our results show how protein aggregation can induce bacteria agglutination and cell death. Using confocal and total internal reflection fluorescence microscopy we have tracked the formation in situ of protein amyloid-like aggregates at the bacteria surface and on membrane models. In both cases, fibrillar aggregates able to bind to amyloid diagnostic dyes were detected. Additionally, a single point mutation (Ile13 to Ala) can suppress the protein amyloid behavior, abolishing the agglutinating activity and impairing the antimicrobial action. The mutant is also defective in triggering both leakage and lipid vesicle aggregation. We conclude that ECP aggregation at the bacterial surface is essential for its cytotoxicity. Hence, we propose here a new prospective biological function for amyloid-like aggregates with potential biological relevance.

Glycosaminoglycans (GAGs) are essential molecules that regulate diverse biological processes including cell adhesion, differentiation, signaling and growth, by interaction with a wide variety of proteins. However, despite the efforts committed to understand the molecular nature of the interactions in protein-GAG complexes, the answer to this question remains elusive.In the present study the interphases of 20 heparin-binding proteins have been analyzed searching for a conserved structural pattern. We have found that a structural motif encompassing one polar and two cationic residues (which has been named the CPC clip motif) is conserved among all the proteins deposited in the PDB. The distances between the α carbons and the side chain center of gravity of the residues composing this motif are also conserved. Furthermore, this pattern can be found in other proteins suggested to bind heparin for which no structural information is available. Hence we propose that the CPC clip motif, working like a staple, is a primary contributor to the attachment of heparin and other sulfated GAGs to heparin-binding proteins.

The increasing rate in antibiotic-resistant bacterial strains has become an imperative health issue. Thus, pharmaceutical industries have focussed their efforts to find new potent, non-toxic compounds to treat bacterial infections. Antimicrobial peptides (AMPs) are promising candidates in the fight against antibiotic-resistant pathogens due to their low toxicity, broad range of activity and unspecific mechanism of action. In this context, bioinformatics' strategies can inspire the design of new peptide leads with enhanced activity. Here, we describe an artificial neural network approach, based on the AMP's physicochemical characteristics, that is able not only to identify active peptides but also to assess its antimicrobial potency. The physicochemical properties considered are directly derived from the peptide sequence and comprise a complete set of parameters that accurately describe AMPs. Most interesting, the results obtained dovetail with a model for the AMP's mechanism of action that takes into account new concepts such as peptide aggregation. Moreover, this classification system displays high accuracy and is well correlated with the experimentally reported data. All together, these results suggest that the physicochemical properties of AMPs determine its action. In addition, we conclude that sequence derived parameters are enough to characterize antimicrobial peptides.