Mining human microbiomes reveals an untapped source of peptide antibiotics.

Drug-resistant bacteria are outpacing traditional antibiotic discovery efforts. Here, we computationally screened 444,054 previously reported putative small protein families from 1,773 human metagenomes for antimicrobial properties, identifying 323 candidates encoded in small open reading frames (smORFs). To test our computational predictions, 78 peptides were synthesized and screened for antimicrobial activity in vitro, with 70.5% displaying antimicrobial activity. As these compounds were different compared with previously reported antimicrobial peptides, we termed them smORF-encoded peptides (SEPs). SEPs killed bacteria by targeting their membrane, synergizing with each other, and modulating gut commensals, indicating a potential 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. Our report supports the existence of hundreds of antimicrobials in the human microbiome amenable to clinical translation.

Discovery of antimicrobial peptides in the global microbiome with machine learning.

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine-learning-based approach to predict antimicrobial peptides (AMPs) within the global microbiome and leverage a vast dataset of 63,410 metagenomes and 87,920 prokaryotic genomes from environmental and host-associated habitats to create the AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, few of which match existing databases. AMPSphere provides insights into the evolutionary origins of peptides, including by duplication or gene truncation of longer sequences, and we observed that AMP production varies by habitat. To validate our predictions, we synthesized and tested 100 AMPs against clinically relevant drug-resistant pathogens and human gut commensals both in vitro and in vivo. A total of 79 peptides were active, with 63 targeting pathogens. These active AMPs exhibited antibacterial activity by disrupting bacterial membranes. In conclusion, our approach identified nearly one million prokaryotic AMP sequences, an open-access resource for antibiotic discovery.

Engineering Phage Host-Range and Suppressing Bacterial Resistance through Phage Tail Fiber Mutagenesis.

The rapid emergence of antibiotic-resistant infections is prompting increased interest in phage-based antimicrobials. However, acquisition of resistance by bacteria is a major issue in the successful development of phage therapies. Through natural evolution and structural modeling, we identified host-range-determining regions (HRDRs) in the T3 phage tail fiber protein and developed a high-throughput strategy to genetically engineer these regions through site-directed mutagenesis. Inspired by antibody specificity engineering, this approach generates deep functional diversity while minimizing disruptions to the overall tail fiber structure, resulting in synthetic "phagebodies." We showed that mutating HRDRs yields phagebodies with altered host-ranges, and select phagebodies enable long-term suppression of bacterial growth in vitro, by preventing resistance appearance, and are functional in vivo using a murine model. We anticipate that this approach may facilitate the creation of next-generation antimicrobials that slow resistance development and could be extended to other viral scaffolds for a broad range of applications.

Impact of natural selection on global patterns of genetic variation and association with clinical phenotypes at genes involved in SARS-CoV-2 infection.

Human genomic diversity has been shaped by both ancient and ongoing challenges from viruses. The current coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a devastating impact on population health. However, genetic diversity and evolutionary forces impacting host genes related to SARS-CoV-2 infection are not well understood. We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (angiotensin converting enzyme 2 [ACE2], transmembrane protease serine 2 [TMPRSS2], dipeptidyl peptidase 4 [DPP4], and lymphocyte antigen 6 complex locus E [LY6E]). We analyzed data from 2,012 ethnically diverse Africans and 15,977 individuals of European and African ancestry with electronic health records and integrated with global data from the 1000 Genomes Project. At ACE2, we identified 41 nonsynonymous variants that were rare in most populations, several of which impact protein function. However, three nonsynonymous variants (rs138390800, rs147311723, and rs145437639) were common among central African hunter-gatherers from Cameroon (minor allele frequency 0.083 to 0.164) and are on haplotypes that exhibit signatures of positive selection. We identify signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2, we identified 13 amino acid changes that are adaptive and specific to the human lineage compared with the chimpanzee genome. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19. Our study provides insights into global variation at host genes related to SARS-CoV-2 infection, which have been shaped by natural selection in some populations, possibly due to prior viral infections.

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.

Interfacial rheology of lanthanide binding peptide surfactants at the air-water interface.

Peptide surfactants (PEPS) are studied to capture and retain rare earth elements (REEs) at air-water interfaces to enable REE separations. Peptide sequences, designed to selectively bind REEs, depend crucially on the position of ligands within their binding loop domain. These ligands form a coordination sphere that wraps and retains the cation. We study variants of lanthanide binding tags (LBTs) designed to complex strongly with Tb3+. The peptide LBT5- (with net charge -5) is known to bind Tb3+ and adsorb with more REE cations than peptide molecules, suggesting that undesired non-specific coulombic interactions occur. Rheological characterization of interfaces of LBT5- and Tb3+ solutions reveal the formation of an interfacial gel. To probe whether this gelation reflects chelation among intact adsorbed LBT5-:Tb3+ complexes or destruction of the binding loop, we study a variant, LBT3-, designed to form net neutral LBT3-:Tb3+ complexes. Solutions of LBT3- and Tb3+ form purely viscous layers in the presence of excess Tb3+, indicating that each peptide binds a single REE in an intact coordination sphere. We introduce the variant RR-LBT3- with net charge -3 and anionic ligands outside of the coordination sphere. We find that such exposed ligands promote interfacial gelation. Thus, a nuanced requirement for interfacial selectivity of PEPS is proposed: that anionic ligands outside of the coordination sphere must be avoided to prevent the non-selective recruitment of REE cations. This view is supported by simulation, including interfacial molecular dynamics simulations, and interfacial metadynamics simulations of the free energy landscape of the binding loop conformational space.

Venetoclax for pediatric patients with newly diagnosed acute myeloid leukemia.

This retrospective study at the University of Texas MD Anderson Cancer Center evaluated frontline venetoclax combination therapy in 11 pediatric/adolescent patients with acute myeloid leukemia (AML). Despite the small sample size and retrospective nature, the treatment demonstrated safety and potential efficacy, with most patients achieving early complete remission. Adverse events were consistent with other AML therapies, and no discontinuations due to toxicity occurred. While acknowledging study limitations, including selection bias and diverse concurrent therapies, this research underscores the promising role of venetoclax in pediatric AML. Further investigation is crucial to validate its long-term efficacy in this population.

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.

Development of a dry eye index as a new biomarker of dry eye disease.

PURPOSE: To evaluate signs and symptoms in patients diagnosed with dry eye disease (DED), divided into dry eye (DE) groups, in order to find a new biomarker that allows an accurate diagnosis, management and classification of DED. METHODS: This cross-sectional, observational study included 71 DED subjects. Subjective symptoms, visual quality and DE signs were assessed using the Ocular Surface Disease Index (OSDI), the Quality of Vision (QoV) questionnaire, best corrected distance visual acuity (VA), functional visual acuity (FVA), contrast sensitivity (CS), high- and low-order corneal aberrations (HOA and LOA, respectively), tear break-up time (TBUT), Meibomian Gland Dysfunction (MGD), Schirmer test, corneal staining, lid wiper epitheliopathy (LWE) and meibography. Participants were classified into three groups based on dryness severity using a cluster analysis, i.e., mild (N = 17, 55.8 ± 15.4 years), moderate (N = 41, 63.5 ± 10.6 years) and severe (N = 13, 65.0 ± 12.0). A new Dry Eye Severity Index (DESI) based on ocular surface signs has been developed and its association with symptoms, visual quality and signs was assessed. Comparisons between groups were made using Kruskal-Wallis and Chi-squared tests. Spearman correlation analysis was also performed. RESULTS: The DESI was based on three tests for DE signs: TBUT, Schirmer test and MGD. The DESI showed significant differences between different pairs of groups: Mild Dryness versus Moderate Dryness (p < 0.001), Mild Dryness versus Severe Dryness (p < 0.001) and Moderate Dryness versus Severe Dryness (p < 0.001). The DESI was significantly correlated with age (rho = -0.30; p = 0.01), OSDI score (rho = -0.32; p = 0.007), QoV score (rho = -0.35; p = 0.003), VA (rho = -0.34; p = 0.003), FVA (rho = -0.38; p = 0.001) and CS (rho = 0.42; p < 0.001) Also, significant differences between the severity groups were found for OSDI and QoV scores, VA, FVA, CS and MGD (p < 0.05). CONCLUSIONS: The DESI has good performance as a biomarker for the diagnosis, classification and management of DED.

Minute-scale detection of SARS-CoV-2 using a low-cost biosensor composed of pencil graphite electrodes.

COVID-19 has led to over 3.47 million deaths worldwide and continues to devastate primarily middle- and low-income countries. High-frequency testing has been proposed as a potential solution to prevent outbreaks. However, current tests are not sufficiently low-cost, rapid, or scalable to enable broad COVID-19 testing. Here, we describe LEAD (Low-cost Electrochemical Advanced Diagnostic), a diagnostic test that detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within 6.5 min and costs $1.50 per unit to produce using easily accessible and commercially available materials. LEAD is highly sensitive toward SARS-CoV-2 spike protein (limit of detection = 229 fg⋅mL-1) and displays an excellent performance profile using clinical saliva (100.0% sensitivity, 100.0% specificity, and 100.0% accuracy) and nasopharyngeal/oropharyngeal (88.7% sensitivity, 86.0% specificity, and 87.4% accuracy) samples. No cross-reactivity was detected with other coronavirus or influenza strains. Importantly, LEAD also successfully diagnosed the highly contagious SARS-CoV-2 B.1.1.7 UK variant. The device presents high reproducibility under all conditions tested and preserves its original sensitivity for 5 d when stored at 4 °C in phosphate-buffered saline. Our low-cost and do-it-yourself technology opens new avenues to facilitate high-frequency testing and access to much-needed diagnostic tests in resource-limited settings and low-income communities.

Pandemic Times and Health Care Exclusion: Attitudes Toward Health Care Exclusion of Undocumented Immigrants.

CONTEXT: Most of the 11 million undocumented immigrants living in the United States are excluded from government healthcare programs. Yet, healthcare inequities pose significant dangers to all members of society during a pandemic. This project explores to what extent undocumented immigrants, in the context of a pandemic, can be seen as deserving of access to government healthcare programs. METHODS: The first survey experiment explores whether work ethic can affect perceptions of undocumented immigrants as deserving of government healthcare programs. The second survey experiment tests to what extent appeals to fairness and self-interest, during a pandemic, shape healthcare deservingness attitudes. FINDINGS: The results show that respondents view undocumented immigrants as less deserving of healthcare than citizens, even when undocumented immigrants have a solid work history. The second survey experiment, however, shows that appeals to fairness and self-interest trigger substantial increases in support for undocumented immigrants, both among Republicans and Democrats. CONCLUSIONS: The results suggest that while undocumented immigrants are seen as less deserving of access, appeals to fairness and self-interest can trigger increased support.

From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance - a Comprehensive Review.

The emergence of drug-resistant bacteria poses a significant challenge to modern medicine. In response, Artificial Intelligence (AI) and Machine Learning (ML) algorithms have emerged as powerful tools for combating antimicrobial resistance (AMR). This review aims to explore the role of AI/ML in AMR management, with a focus on identifying pathogens, understanding resistance patterns, predicting treatment outcomes, and discovering new antibiotic agents. Recent advancements in AI/ML have enabled the efficient analysis of large datasets, facilitating the reliable prediction of AMR trends and treatment responses with minimal human intervention. ML algorithms can analyze genomic data to identify genetic markers associated with antibiotic resistance, enabling the development of targeted treatment strategies. Additionally, AI/ML techniques show promise in optimizing drug administration and developing alternatives to traditional antibiotics. By analyzing patient data and clinical outcomes, these technologies can assist healthcare providers in diagnosing infections, evaluating their severity, and selecting appropriate antimicrobial therapies. While integration of AI/ML in clinical settings is still in its infancy, advancements in data quality and algorithm development suggest that widespread clinical adoption is forthcoming. In conclusion, AI/ML holds significant promise for improving AMR management and treatment outcome.

The pupillary dilation reflex to a nociceptive stimulus as a tool for analgesia management: A diagnostic study.

BACKGROUND: More than 70% of patients demonstrate pain after endotracheal aspiration. Tools are needed to objectify the need for analgesia in non-communicative critically ill patients. OBJECTIVE: The objective of this study was to identify the lowest intensity electrical stimulus for detecting pain before daily care interventions. METHODS: Study of diagnostic tests to assess pupillometry to detect pain through the pupillary dilation response to noxious stimuli versus the Behavioural Pain Scale. Patients older than 18 years, under analgosedation, subjected to invasive ventilation, baseline Behavioural Pain Scale of 3, and Richmond Agitation-Sedation Scale between -1 and -4 were studied. We assessed the Behavioural Pain Scale and the pupillary dilation response to 10, 20, 30, and 40 mA stimuli. We studied the diagnostic performance based on sensitivity and specificity, negative predictive value, positive predictive value, and accuracy of the selected points after the different stimulations. AlgiScan® Pupillometer measured the pupillary dilation response. The presence of pain was considered as a Behavioural Pain Scale score of ≥4. Significance was defined as p <0.05. RESULTS: Measurements were performed on 31 patients. In the 20 mA stimulus, we found an area under the curve of 0.85 (0.69-1.0). The cut-off point of pupillary dilation was 11.5%, with a sensitivity of 100% (34.2-100) and a specificity of 75.9% (57.9-87.8). This point had an accuracy of 77.4 (60.2-88.6) and a Youden's Index of 0.8. CONCLUSIONS: Pupillary variation measurement during a 20 mA stimulus could help assess the need for analgesia before potentially painful interventions. Further studies are needed to confirm this. REGISTRATION: Phase 1 of the project PUPIPAIN ClinicalTrials.gov Identifier: NCT04078113.

Probiotics: insights and new opportunities for Clostridioides difficile intervention.

Clostridioides difficile infection (CDI) is a life-threatening disease caused by the Gram-positive, opportunistic intestinal pathogen C. difficile. Despite the availability of antimicrobial drugs to treat CDI, such as vancomycin, metronidazole, and fidaxomicin, recurrence of infection remains a significant clinical challenge. The use of live commensal microorganisms, or probiotics, is one of the most investigated non-antibiotic therapeutic options to balance gastrointestinal (GI) microbiota and subsequently tackle dysbiosis. In this review, we will discuss major commensal probiotic strains that have the potential to prevent and/or treat CDI and its recurrence, reassess the efficacy of probiotics supplementation as a CDI intervention, delve into lessons learned from probiotic modulation of the immune system, explore avenues like genome-scale metabolic network reconstructions, genome sequencing, and multi-omics to identify novel strains and understand their functionality, and discuss the current regulatory framework, challenges, and future directions.

Hydrogel-based biocontainment of bacteria for continuous sensing and computation.

Genetically modified microorganisms (GMMs) can enable a wide range of important applications including environmental sensing and responsive engineered living materials. However, containment of GMMs to prevent environmental escape and satisfy regulatory requirements is a bottleneck for real-world use. While current biochemical strategies restrict unwanted growth of GMMs in the environment, there is a need for deployable physical containment technologies to achieve redundant, multi-layered and robust containment. We developed a hydrogel-based encapsulation system that incorporates a biocompatible multilayer tough shell and an alginate-based core. This deployable physical containment strategy (DEPCOS) allows no detectable GMM escape, bacteria to be protected against environmental insults including antibiotics and low pH, controllable lifespan and easy retrieval of genomically recoded bacteria. To highlight the versatility of DEPCOS, we demonstrated that robustly encapsulated cells can execute useful functions, including performing cell-cell communication with other encapsulated bacteria and sensing heavy metals in water samples from the Charles River.

Mini-hyper CVD + CRIB (condensed rituximab, inotuzumab ozogamicin, and blinatumomab) for refractory pediatric B-acute lymphoblastic leukemia.

Relapsed or refractory pediatric patients with B-acute lymphoblastic leukemia (B-ALL) have high rates of toxicities and relapse, and novel therapy is needed. We present a case of a 5-year-old male child with high-risk B-ALL that was refractory to several re-induction regimens. He was put into minimal residual disease-negative remission after re-induction with chemotherapy plus overlapping rituximab, inotuzumab ozogamicin, and blinatumomab, termed mini-hyper-CVD (cyclophosphamide, vincristine, and dexamethasone) plus CRIB (condensed rituximab, inotuzumab ozogamicin, and blinatumomab). This regimen was well tolerated, and he received his transplant and engrafted with no significant infections, toxicities, or sinusoidal obstruction syndrome. This is the first reported use of a condensed sequential immunotherapy/chemotherapy regimen in a pediatric leukemia patient.

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.

Repurposing a peptide toxin from wasp venom into antiinfectives with dual antimicrobial and immunomodulatory properties.

Novel antibiotics are urgently needed to combat multidrug-resistant pathogens. Venoms represent previously untapped sources of novel drugs. Here we repurposed mastoparan-L, the toxic active principle derived from the venom of the wasp Vespula lewisii, into synthetic antimicrobials. We engineered within its N terminus a motif conserved among natural peptides with potent immunomodulatory and antimicrobial activities. The resulting peptide, mast-MO, adopted an α-helical structure as determined by NMR, exhibited increased antibacterial properties comparable to standard-of-care antibiotics both in vitro and in vivo, and potentiated the activity of different classes of antibiotics. Mechanism-of-action studies revealed that mast-MO targets bacteria by rapidly permeabilizing their outer membrane. In animal models, the peptide displayed direct antimicrobial activity, led to enhanced ability to attract leukocytes to the infection site, and was able to control inflammation. Permutation studies depleted the remaining toxicity of mast-MO toward human cells, yielding derivatives with antiinfective activity in animals. We demonstrate a rational design strategy for repurposing venoms into promising antimicrobials.

Emerging Frontiers in Microbiome Engineering.

The gut microbiome has a significant impact on health and disease and can actively contribute to obesity, diabetes, inflammatory bowel disease, cardiovascular disease, and neurological disorders. We do not yet have the necessary tools to fine-tune the microbial communities that constitute the microbiome, though such tools could unlock extensive benefits to human health. Here, we provide an overview of the current state of technological tools that may be used for microbiome engineering. These tools can enable investigators to define the parameters of a healthy microbiome and to determine how gut bacteria may contribute to the etiology of a variety of diseases. These tools may also allow us to explore the exciting prospect of developing targeted therapies and personalized treatments for microbiome-linked diseases.

Biologically Active Peptides from Venoms: Applications in Antibiotic Resistance, Cancer, and Beyond.

Peptides are potential therapeutic alternatives against global diseases, such as antimicrobial-resistant infections and cancer. Venoms are a rich source of bioactive peptides that have evolved over time to act on specific targets of the prey. Peptides are one of the main components responsible for the biological activity and toxicity of venoms. South American organisms such as scorpions, snakes, and spiders are important producers of a myriad of peptides with different biological activities. In this review, we report the main venom-derived peptide families produced from South American organisms and their corresponding activities and biological targets.