Polyproline peptide targets Klebsiella pneumoniae polysaccharides to collapse biofilms.

Hypervirulent Klebsiella pneumoniae is known for its increased extracellular polysaccharide production. Biofilm matrices of hypervirulent K. pneumoniae have increased polysaccharide abundance and are uniquely susceptible to disruption by peptide bactenecin 7 (bac7 (1-35)). Here, using confocal microscopy, we show that polysaccharides within the biofilm matrix collapse following bac7 (1-35) treatment. This collapse led to the release of cells from the biofilm, which were then killed by the peptide. Characterization of truncated peptide analogs revealed that their interactions with polysaccharide were responsible for the biofilm matrix changes that accompany bac7 (1-35) treatment. Ultraviolet photodissociation mass spectrometry with the parental peptide or a truncated analog bac7 (10-35) reveal the important regions for bac7 (1-35) complexing with polysaccharides. Finally, we tested bac7 (1-35) using a murine skin abscess model and observed a significant decrease in the bacterial burden. These findings unveil the potential of bac7 (1-35) polysaccharide interactions to collapse K. pneumoniae biofilms.

Peptides from non-immune proteins target infections through antimicrobial and immunomodulatory properties.

Encrypted peptides have been recently described as a new class of antimicrobial molecules. They have been proposed to play a role in host immunity and as alternatives to conventional antibiotics. Intriguingly, many of these peptides are found embedded in proteins unrelated to the immune system, suggesting that immunological responses may extend beyond traditional host immunity proteins. To test this idea, here we synthesized and tested representative peptides derived from non-immune proteins for their ability to exert antimicrobial and immunomodulatory properties. Our experiments revealed that most of the tested peptides from non-immune proteins, derived from structural proteins as well as proteins from the nervous and visual systems, displayed potent in vitro antimicrobial activity. These molecules killed bacterial pathogens by targeting their membrane, and those originating from the same region of the body exhibited synergistic effects when combined. Beyond their antimicrobial properties, nearly 90% of the peptides tested exhibited immunomodulatory effects, modulating inflammatory mediators such as IL-6, TNF-α, and MCP-1. Moreover, eight of the peptides identified, collagenin 3 and 4, zipperin-1 and 2, and immunosin-2, 3, 12, and 13, displayed anti-infective efficacy in two different preclinical mouse models, reducing bacterial infections by up to four orders of magnitude. Altogether, our results support the hypothesis that peptides from non-immune proteins may play a role in host immunity. These results potentially expand our notion of the immune system to include previously unrecognized proteins and peptides that may be activated upon infection to confer protection to the host.

El papel de la impulsividad en la orientación al suicidio de universitarios con antecedentes de conducta autolesiva / The role of impulsivity in suicidal orientation of university students with a history of self-injurious behavior

El objetivo de esta investigación fue describir el efecto de la depresión, la desesperanza y la impulsividad sobre la orientación al suicidio y el papel de la impulsividad como mediador de la orientación suicida en universitarios con antecedentes de conductas autolesivas. Participaron 1.645 jóvenes entre los 18 y 29 años, de dos ciudades colombianas. Se seleccionaron 218 jóvenes (M= 21,00; DT= 2,99) que informaron de al menos un intento de suicidio en el último año, quienes contestaron el “Inventario de orientación suicida”, la “Escala de desesperanza de Beck”, el “Inventario de depresión de Beck” y la “Escala de impulsividad de Barratt”. La depresión, la desesperanza y la impulsividad explicaron el 63% de la variación de la orientación al suicidio (R2= 0,635; IC 95% [0,555; 0,713]; p= 0,001). La impulsividad medió con depresión en aquellos casos en los que la orientación suicida era alta, cuyos efectos totales, directos e indirectos, fueron estadísticamente significativos (p< 0,001). La impulsividad desempeña un papel mediador entre la depresión y la desesperanza en la predicción de la orientación suicida.(AU)

The aim of this research was to describe the effect of depression,hopelessness, and impulsivity on orientation to suicide and the role of impulsivityas a mediator of suicidal orientation in university students with a history of self-injury behaviors. 1645 young people between 18 and 29 years old participated,from two Colombian cities. 218 young people were selected (M= 21.00; SD= 2.99)who reported at least one suicide attempt in the last year, who answered the“Suicidal Orientation Inventory”, the “Beck Hopelessness Scale”, the “BeckDepression Inventory” and the “Barratt Impulsivity Scale”. Depression,hopelessness, and impulsivity explained 63% of the variation in suicidal orientation (R 2 = .635, IC 95% [.555, .713], p= .001). Impulsivity mediated with depression inthose cases in which suicidal orientation was high, whose total, direct and indirecteffects were statistically significant (p< .001). Impulsivity plays a mediating rolebetween depression and hopelessness in predicting suicidal orientation.K EY WORDS : depression, hopelessness, impulsivity, suicidality, college youth.(AU)

Biological Markers of High-Risk Childhood Acute Lymphoblastic Leukemia.

Childhood acute lymphoblastic leukemia (ALL) has witnessed substantial improvements in prognosis; however, a subset of patients classified as high-risk continues to face higher rates of relapse and increased mortality. While the National Cancer Institute (NCI) criteria have traditionally guided risk stratification based on initial clinical information, recent advances highlight the pivotal role of biological markers in shaping the prognosis of childhood ALL. This review delves into the emerging understanding of high-risk childhood ALL, focusing on molecular, cytogenetic, and immunophenotypic markers. These markers not only contribute to unraveling the underlying mechanisms of the disease, but also shed light on specific clinical patterns that dictate prognosis. The paradigm shift in treatment strategies, exemplified by the success of tyrosine kinase inhibitors in Philadelphia chromosome-positive leukemia, underscores the importance of recognizing and targeting precise risk factors. Through a comprehensive exploration of high-risk childhood ALL characteristics, this review aims to enhance our comprehension of the disease, offering insights into its molecular landscape and clinical intricacies in the hope of contributing to future targeted and tailored therapies.

Challenges in computational discovery of bioactive peptides in 'omics data.

Peptides have a plethora of activities in biological systems that can potentially be exploited biotechnologically. Several peptides are used clinically, as well as in industry and agriculture. The increase in available 'omics data has recently provided a large opportunity for mining novel enzymes, biosynthetic gene clusters, and molecules. While these data primarily consist of DNA sequences, other types of data provide important complementary information. Due to their size, the approaches proven successful at discovering novel proteins of canonical size cannot be naïvely applied to the discovery of peptides. Peptides can be encoded directly in the genome as short open reading frames (smORFs), or they can be derived from larger proteins by proteolysis. Both of these peptide classes pose challenges as simple methods for their prediction result in large numbers of false positives. Similarly, functional annotation of larger proteins, traditionally based on sequence similarity to infer orthology and then transferring functions between characterized proteins and uncharacterized ones, cannot be applied for short sequences. The use of these techniques is much more limited and alternative approaches based on machine learning are used instead. Here, we review the limitations of traditional methods as well as the alternative methods that have recently been developed for discovering novel bioactive peptides with a focus on prokaryotic genomes and metagenomes.

Synthetic angiotensin II peptide derivatives confer protection against cerebral and severe non-cerebral malaria in murine models.

Malaria can have severe long-term effects. Even after treatment with antimalarial drugs eliminates the parasite, survivors of cerebral malaria may suffer from irreversible brain damage, leading to cognitive deficits. Angiotensin II, a natural human peptide hormone that regulates blood pressure, has been shown to be active against Plasmodium spp., the etiologic agent of malaria. Here, we tested two Ang II derivatives that do not elicit vasoconstriction in mice: VIPF, a linear tetrapeptide, which constitutes part of the hydrophobic portion of Ang II; and Ang II-SS, a disulfide-bridged derivative. The antiplasmodial potential of both peptides was evaluated with two mouse models: an experimental cerebral malaria model and a mouse model of non-cerebral malaria. The latter consisted of BALB/c mice infected with Plasmodium berghei ANKA. The peptides had no effect on mean blood pressure and significantly reduced parasitemia in both mouse models. Both peptides reduced the SHIRPA score, an assay used to assess murine health and behavior. However, only the constrained derivative (Ang II-SS), which was also resistant to proteolytic degradation, significantly increased mouse survival. Here, we show that synthetic peptides derived from Ang II are capable of conferring protection against severe manifestations of malaria in mouse models while overcoming the vasoconstrictive side effects of the parent peptide.

Feasible diet and circadian interventions reduce in vivo progression of FLT3-ITD-positive acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) with an internal tandem duplication in the fms-like tyrosine kinase receptor 3 gene (FLT3-ITD) is associated with poor survival, and few studies have examined the impact of modifiable behaviors, such as nutrient quality and timing, in this subset of acute leukemia. METHODS: The influence of diet composition (low-sucrose and/or low-fat diets) and timing of diet were tested in tandem with anthracycline treatment in orthotopic xenograft mouse models. A pilot clinical study to test receptivity of pediatric leukemia patients to macronutrient matched foods was conducted. A role for the circadian protein, BMAL1 (brain and muscle ARNT-like 1), in effects of diet timing was studied by overexpression in FLT3-ITD-bearing AML cells. RESULTS: Reduced tumor burden in FLT3-ITD AML-bearing mice was observed with interventions utilizing low-sucrose and/or low-fat diets, or time-restricted feeding (TRF) compared to mice fed normal chow ad libitum. In a tasting study, macronutrient matched low-sucrose and low-fat meals were offered to pediatric acute leukemia patients who largely reported liking the meals. Expression of the circadian protein, BMAL1, was heightened with TRF and the low-sucrose diet. BMAL1 overexpression and treatment with a pharmacological inducer of BMAL1 was cytotoxic to FLT3-ITD AML cells. CONCLUSIONS: Mouse models for FLT3-ITD AML show that diet composition and timing slows progression of FLT3-ITD AML growth in vivo, potentially mediated by BMAL1. These interventions to enhance therapy efficacy show preliminary feasibility, as pediatric leukemia patients responded favorable to preparation of macronutrient matched meals.

Low-Cost Biosensor Technologies for Rapid Detection of COVID-19 and Future Pandemics.

Many systems have been designed for the detection of SARS-CoV-2, which is the virus that causes COVID-19. SARS-CoV-2 is readily transmitted, resulting in the rapid spread of disease in human populations. Frequent testing at the point of care (POC) is a key aspect for controlling outbreaks caused by SARS-CoV-2 and other emerging pathogens, as the early identification of infected individuals can then be followed by appropriate measures of isolation or treatment, maximizing the chances of recovery and preventing infectious spread. Diagnostic tools used for high-frequency testing should be inexpensive, provide a rapid diagnostic response without sophisticated equipment, and be amenable to manufacturing on a large scale. The application of these devices should enable large-scale data collection, help control viral transmission, and prevent disease propagation. Here we review functional nanomaterial-based optical and electrochemical biosensors for accessible POC testing for COVID-19. These biosensors incorporate nanomaterials coupled with paper-based analytical devices and other inexpensive substrates, traditional lateral flow technology (antigen and antibody immunoassays), and innovative biosensing methods. We critically discuss the advantages and disadvantages of nanobiosensor-based approaches compared to widely used technologies such as PCR, ELISA, and LAMP. Moreover, we delineate the main technological, (bio)chemical, translational, and regulatory challenges associated with developing functional and reliable biosensors, which have prevented their translation into the clinic. Finally, we highlight how nanobiosensors, given their unique advantages over existing diagnostic tests, may help in future pandemics.

Recombinant production of antimicrobial peptides in plants.

Classical plant breeding methods are limited in their ability to confer disease resistance on plants. However, in recent years, advancements in molecular breeding and biotechnological have provided new approaches to overcome these limitations and protect plants from disease. Antimicrobial peptides (AMPs) constitute promising agents that may be able to protect against infectious agents. Recently, peptides have been recombinantly produced in plants at scale and low cost. Because AMPs are less likely than conventional antimicrobials to elicit resistance of pathogenic bacteria, they open up exciting new avenues for agricultural applications. Here, we review recent advances in the design and production of bioactive recombinant AMPs that can effectively protect crop plants from diseases.

Computational Design of Peptides for Biomaterials Applications.

Computer-aided molecular design and protein engineering emerge as promising and active subjects in bioengineering and biotechnological applications. On one hand, due to the advancing computing power in the past decade, modeling toolkits and force fields have been put to use for accurate multiscale modeling of biomolecules including lipid, protein, carbohydrate, and nucleic acids. On the other hand, machine learning emerges as a revolutionary data analysis tool that promises to leverage physicochemical properties and structural information obtained from modeling in order to build quantitative protein structure-function relationships. We review recent computational works that utilize state-of-the-art computational methods to engineer peptides and proteins for various emerging biomedical, antimicrobial, and antifreeze applications. We also discuss challenges and possible future directions toward developing a roadmap for efficient biomolecular design and engineering.

Antibiotic failure: Beyond antimicrobial resistance.

Despite significant progress in antibiotic discovery, millions of lives are lost annually to infections. Surprisingly, the failure of antimicrobial treatments to effectively eliminate pathogens frequently cannot be attributed to genetically-encoded antibiotic resistance. This review aims to shed light on the fundamental mechanisms contributing to clinical scenarios where antimicrobial therapies are ineffective (i.e., antibiotic failure), emphasizing critical factors impacting this under-recognized issue. Explored aspects include biofilm formation and sepsis, as well as the underlying microbiome. Therapeutic strategies beyond antibiotics, are examined to address the dimensions and resolution of antibiotic failure, actively contributing to this persistent but escalating crisis. We discuss the clinical relevance of antibiotic failure beyond resistance, limited availability of therapies, potential of new antibiotics to be ineffective, and the urgent need for novel anti-infectives or host-directed therapies directly addressing antibiotic failure. Particularly noteworthy is multidrug adaptive resistance in biofilms that represent 65 % of infections, due to the lack of approved therapies. Sepsis, responsible for 19.7 % of all deaths (as well as severe COVID-19 deaths), is a further manifestation of this issue, since antibiotics are the primary frontline therapy, and yet 23 % of patients succumb to this condition.

Deep learning tools to accelerate antibiotic discovery.

INTRODUCTION: As machine learning (ML) and artificial intelligence (AI) expand to many segments of our society, they are increasingly being used for drug discovery. Recent deep learning models offer an efficient way to explore high-dimensional data and design compounds with desired properties, including those with antibacterial activity. AREAS COVERED: This review covers key frameworks in antibiotic discovery, highlighting physicochemical features and addressing dataset limitations. The deep learning approaches here described include discriminative models such as convolutional neural networks, recurrent neural networks, graph neural networks, and generative models like neural language models, variational autoencoders, generative adversarial networks, normalizing flow, and diffusion models. As the integration of these approaches in drug discovery continues to evolve, this review aims to provide insights into promising prospects and challenges that lie ahead in harnessing such technologies for the development of antibiotics. EXPERT OPINION: Accurate antimicrobial prediction using deep learning faces challenges such as imbalanced data, limited datasets, experimental validation, target strains, and structure. The integration of deep generative models with bioinformatics, molecular dynamics, and data augmentation holds the potential to overcome these challenges, enhance model performance, and utlimately accelerate antimicrobial discovery.

Molecular hybridization strategy for tuning bioactive peptide function.

The physicochemical and structural properties of antimicrobial peptides (AMPs) determine their mechanism of action and biological function. However, the development of AMPs as therapeutic drugs has been traditionally limited by their toxicity for human cells. Tuning the physicochemical properties of such molecules may abolish toxicity and yield synthetic molecules displaying optimal safety profiles and enhanced antimicrobial activity. Here, natural peptides were modified to improve their activity by the hybridization of sequences from two different active peptide sequences. Hybrid AMPs (hAMPs) were generated by combining the amphipathic faces of the highly toxic peptide VmCT1, derived from scorpion venom, with parts of four other naturally occurring peptides having high antimicrobial activity and low toxicity against human cells. This strategy led to the design of seven synthetic bioactive variants, all of which preserved their structure and presented increased antimicrobial activity (3.1-128 µmol L-1). Five of the peptides (three being hAMPs) presented high antiplasmodial at 0.8 µmol L-1, and virtually no undesired toxic effects against red blood cells. In sum, we demonstrate that peptide hybridization is an effective strategy for redirecting biological activity to generate novel bioactive molecules with desired properties.

Synergistic Combination of Antimicrobial Peptides and Cationic Polyitaconates in Multifunctional PLA Fibers.

Combining different antimicrobial agents has emerged as a promising strategy to enhance efficacy and address resistance evolution. In this study, we investigated the synergistic antimicrobial effect of a cationic biobased polymer and the antimicrobial peptide (AMP) temporin L, with the goal of developing multifunctional electrospun fibers for potential biomedical applications, particularly in wound dressing. A clickable polymer with pendent alkyne groups was synthesized by using a biobased itaconic acid building block. Subsequently, the polymer was functionalized through click chemistry with thiazolium groups derived from vitamin B1 (PTTIQ), as well as a combination of thiazolium and AMP temporin L, resulting in a conjugate polymer-peptide (PTTIQ-AMP). The individual and combined effects of the cationic PTTIQ, Temporin L, and PTTIQ-AMP were evaluated against Gram-positive and Gram-negative bacteria as well as Candida species. The results demonstrated that most combinations exhibited an indifferent effect, whereas the covalently conjugated PTTIQ-AMP displayed an antagonistic effect, potentially attributed to the aggregation process. Both antimicrobial compounds, PTTIQ and temporin L, were incorporated into poly(lactic acid) electrospun fibers using the supercritical solvent impregnation method. This approach yielded fibers with improved antibacterial performance, as a result of the potent activity exerted by the AMP and the nonleaching nature of the cationic polymer, thereby enhancing long-term effectiveness.

Frontline Hyper-CVAD Plus Venetoclax for Pediatric Blastic Plasmacytoid Dendritic Cell Neoplasm.

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematologic malignancy, especially in pediatrics, that can involve the bone marrow, skin, lymph nodes, and central nervous system (CNS). Given its variable clinical presentation, coupled with an immunohistochemistry pattern (CD4, CD56, TCF4, TCL-1, and CD123 positivity) that differs from other myeloid neoplasms, the diagnosis of BPDCN can be missed. Limited data are available to guide the treatment of pediatric BPDCN. Herein, we report a case of a pediatric patient who had BPDCN with central nervous system, orbital, and skin involvement. This patient achieved complete remission after receiving modified hyper-CVAD (hyperfractionated cyclophosphamide, vincristine, doxorubicin, and dexamethasone with venetoclax and intrathecal chemotherapy. He remains disease-free 200 days after receiving a stem cell transplant. This represents the first known published pediatric case using a modified hyper-CVAD plus venetoclax regimen for treating a pediatric BPDCN patient in the frontline setting.

Human gut metagenomic mining reveals an untapped source of peptide antibiotics.

Drug-resistant bacteria are outpacing traditional antibiotic discovery efforts. Here, we computationally mined 444,054 families of putative small proteins from 1,773 human gut metagenomes, identifying 323 peptide antibiotics encoded in small open reading frames (smORFs). To test our computational predictions, 78 peptides were synthesized and screened for antimicrobial activity in vitro, with 59% displaying activity against either pathogens or commensals. Since these peptides were unique compared to previously reported antimicrobial peptides, we termed them smORF-encoded peptides (SEPs). SEPs killed bacteria by targeting their membrane, synergized with each other, and modulated gut commensals, indicating that they may play a role in reconfiguring microbiome communities in addition to counteracting pathogens. The lead candidates were anti-infective in both murine skin abscess and deep thigh infection models. Notably, prevotellin-2 from Prevotella copri presented activity comparable to the commonly used antibiotic polymyxin B. We report the discovery of hundreds of peptide sequences in the human gut.