Vibrational, optical, and photocatalytic properties of ZnO/layered carbon nanocomposite synthesized by ball milling.

ZnO/layered carbon nanocomposites with varied sizes of ZnO nanoparticles (NPs) were synthesized by mechanical milling of mixture of ZnO NPs and carbon NPs. The NP size of ZnO was controlled with average particle sizes about 19.33, 21.87, 24.21, and 27.89 nm by varying the concentrations of carbon NPs viz 0, 2, 5, and 10 weight percent, respectively, in the mixture. Presence of carbon with ZnO in the form of composite also resulted in the enhanced shift of the band gap of ZnO due to the optical transitions in the impurity states or presence of carbon as compared to the ZnO size change alone. Additionally, the enhancement of absorbance in the visible region with an increase in carbon content was observed. Such an increase in absorbance can enhance the photocatalytic activity of ZnO NPs. Raman bands for ZnO NPs also were found to shift faster in the presence of layered carbon. The quenching of visible photoluminescence emission of ZnO NPs with an increase in concentration of carbon NPs in the composite indicated the phenomenon associated with transfer of electrons from ZnO to layered carbon helping the separation of photo-generated electrons and holes in ZnO and can lead to enhancement of the photocatalytic activity of ZnO NPs. In the photocatalytic studies, it was observed that the degradation of methylene blue (MB) dye was significantly enhanced by the increase of content of layered carbon in the nanocomposite. The sample containing 10% carbon showed the highest adsorption in dark conditions which was up to 60% of the starting strength and this was further enhanced to 88% in the presence of UV radiation. Enhanced adsorption of MB dye and the effective separation of electron-hole pairs due to charge transfer were believed to be the main causes behind such kind of improvement in the photocatalytic effects.

PERCEPTION predicts patient response and resistance to treatment using single-cell transcriptomics of their tumors.

Tailoring optimal treatment for individual cancer patients remains a significant challenge. To address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression-Based Planning for Treatments In ONcology), a precision oncology computational pipeline. Our approach uses publicly available matched bulk and single-cell (sc) expression profiles from large-scale cell-line drug screens. These profiles help build treatment response models based on patients' sc-tumor transcriptomics. PERCEPTION demonstrates success in predicting responses to targeted therapies in cultured and patient-tumor-derived primary cells, as well as in two clinical trials for multiple myeloma and breast cancer. It also captures the resistance development in patients with lung cancer treated with tyrosine kinase inhibitors. PERCEPTION outperforms published state-of-the-art sc-based and bulk-based predictors in all clinical cohorts. PERCEPTION is accessible at https://github.com/ruppinlab/PERCEPTION . Our work, showcasing patient stratification using sc-expression profiles of their tumors, will encourage the adoption of sc-omics profiling in clinical settings, enhancing precision oncology tools based on sc-omics.

Factors affecting heterogeneity in breast cancer microenvironment: A narrative mini review.

Breast cancer (BC) heterogeneity is a key trait of BC tumors with crucial implications on tumorigenesis, diagnosis, and therapeutic modalities. It is influenced by tumor intrinsic features and by the tumor microenvironment (TME) composition of different intra-tumoral regions, which in turn affect cancer progression within patients. In this mini review, we will highlight the mechanisms that generate cancer heterogeneity in BC and how they affect the responses to cancer therapies.

Assessment of differentially private synthetic data for utility and fairness in end-to-end machine learning pipelines for tabular data.

Differentially private (DP) synthetic datasets are a solution for sharing data while preserving the privacy of individual data providers. Understanding the effects of utilizing DP synthetic data in end-to-end machine learning pipelines impacts areas such as health care and humanitarian action, where data is scarce and regulated by restrictive privacy laws. In this work, we investigate the extent to which synthetic data can replace real, tabular data in machine learning pipelines and identify the most effective synthetic data generation techniques for training and evaluating machine learning models. We systematically investigate the impacts of differentially private synthetic data on downstream classification tasks from the point of view of utility as well as fairness. Our analysis is comprehensive and includes representatives of the two main types of synthetic data generation algorithms: marginal-based and GAN-based. To the best of our knowledge, our work is the first that: (i) proposes a training and evaluation framework that does not assume that real data is available for testing the utility and fairness of machine learning models trained on synthetic data; (ii) presents the most extensive analysis of synthetic dataset generation algorithms in terms of utility and fairness when used for training machine learning models; and (iii) encompasses several different definitions of fairness. Our findings demonstrate that marginal-based synthetic data generators surpass GAN-based ones regarding model training utility for tabular data. Indeed, we show that models trained using data generated by marginal-based algorithms can exhibit similar utility to models trained using real data. Our analysis also reveals that the marginal-based synthetic data generated using AIM and MWEM PGM algorithms can train models that simultaneously achieve utility and fairness characteristics close to those obtained by models trained with real data.

Designing RNA switches for synthetic biology using inverse-RNA-folding.

RNA switches respond to specific ligands to control gene expression. They are widely used in synthetic biology applications and hold potential for future RNA-based therapeutic breakthroughs. However, the crux is their precise design. Here, we will discuss how inverse-RNA-folding could be utilized for the accurate design of RNA switches.

The mature N-termini of Plasmodium effector proteins confer specificity of export.

IMPORTANCE: Malaria parasites export hundreds of proteins to the cytoplasm of the host red blood cells for their survival. A five amino acid sequence, called the PEXEL motif, is conserved among many exported proteins and is thought to be a signal for export. However, the motif is cleaved inside the endoplasmic reticulum of the parasite, and mature proteins starting from the fourth PEXEL residue travel to the parasite periphery for export. We showed that the PEXEL motif is dispensable for export as long as identical mature proteins can be efficiently produced via alternative means in the ER. We also showed that the exported and non-exported proteins are differentiated at the parasite periphery based on their mature N-termini; however, any discernible export signal within that region remained cryptic. Our study resolves a longstanding paradox in PEXEL protein trafficking.

Using Data Science and a Health Equity Lens to Identify Long-COVID Sequelae Among Medically Underserved Populations.

Understanding how post-acute COVID-19 syndrome (PACS or long COVID) manifests among underserved populations, who experienced a disproportionate burden of acute COVID-19, can help providers and policymakers better address this ongoing crisis. To identify clinical sequelae of long COVID among underserved populations treated in the primary care safety net, we conducted a causal impact analysis with electronic health records (EHR) to compare symptoms among community health center patients who tested positive (n=4,091) and negative (n=7,118) for acute COVID-19. We found 18 sequelae with statistical significance and causal dependence among patients who had a visit after 60 days or more following acute COVID-19. These sequelae encompass most organ systems and include breathing abnormalities, malaise and fatigue, and headache. This study adds to current knowledge about how long COVID manifests in a large, underserved population.

Activation of the Plasmodium Egress Effector Subtilisin-Like Protease 1 Is Mediated by Plasmepsin X Destruction of the Prodomain.

Following each round of replication, daughter merozoites of the malaria parasite Plasmodium falciparum escape (egress) from the infected host red blood cell (RBC) by rupturing the parasitophorous vacuole membrane (PVM) and the RBC membrane (RBCM). A proteolytic cascade orchestrated by a parasite serine protease, subtilisin-like protease 1 (SUB1), regulates the membrane breakdown. SUB1 activation involves primary autoprocessing of the 82-kDa zymogen to a 54-kDa (p54) intermediate that remains bound to its inhibitory propiece (p31) postcleavage. A second processing step converts p54 to the terminal 47-kDa (p47) form of SUB1. Although the aspartic protease plasmepsin X (PM X) has been implicated in the activation of SUB1, the mechanism remains unknown. Here, we show that upon knockdown of PM X, the inhibitory p31-p54 complex of SUB1 accumulates in the parasites. Using recombinant PM X and SUB1, we show that PM X can directly cleave both p31 and p54. We have mapped the cleavage sites on recombinant p31. Furthermore, we demonstrate that the conversion of p54 to p47 can be effected by cleavage at either SUB1 or PM X cleavage sites that are adjacent to one another. Importantly, once the p31 is removed, p54 is fully functional inside the parasites, suggesting that the conversion to p47 is dispensable for SUB1 activity. Relief of propiece inhibition via a heterologous protease is a novel mechanism for subtilisin activation. IMPORTANCE Malaria parasites replicate inside a parasitophorous vacuole within the host red blood cells. The exit of mature progeny from the infected host cells is essential for further dissemination. Parasite exit is a highly regulated, explosive process that involves membrane breakdown. To do this, the parasite utilizes a serine protease called SUB1 that proteolytically activates various effector proteins. SUB1 activity is dependent on an upstream protease called PM X, although the mechanism was unknown. Here, we describe the molecular basis for PM X-mediated SUB1 activation. PM X proteolytically degrades the inhibitory segment of SUB1, thereby activating it. The involvement of a heterologous protease is a novel mechanism for subtilisin activation.

A computational approach for the identification of distant homologs of bacterial riboswitches based on inverse RNA folding.

Riboswitches are conserved structural ribonucleic acid (RNA) sensors that are mainly found to regulate a large number of genes/operons in bacteria. Presently, >50 bacterial riboswitch classes have been discovered, but only the thiamine pyrophosphate riboswitch class is detected in a few eukaryotes like fungi, plants and algae. One of the most important challenges in riboswitch research is to discover existing riboswitch classes in eukaryotes and to understand the evolution of bacterial riboswitches. However, traditional search methods for riboswitch detection have failed to detect eukaryotic riboswitches besides just one class and any distant structural homologs of riboswitches. We developed a novel approach based on inverse RNA folding that attempts to find sequences that match the shape of the target structure with minimal sequence conservation based on key nucleotides that interact directly with the ligand. Then, to support our matched candidates, we expanded the results into a covariance model representing similar sequences preserving the structure. Our method transforms a structure-based search into a sequence-based search that considers the conservation of secondary structure shape and ligand-binding residues. This method enables us to identify a potential structural candidate in fungi that could be the distant homolog of bacterial purine riboswitches. Further, phylogenomic analysis and evolutionary distribution of this structural candidate indicate that the most likely point of origin of this structural candidate in these organisms is associated with the loss of traditional purine riboswitches. The computational approach could be applicable to other domains and problems in RNA research.

The Landscape of Expressed Chimeric Transcripts in the Blood of Severe COVID-19 Infected Patients.

The ongoing COVID-19 pandemic caused by SARS-CoV-2 infections has quickly developed into a global public health threat. COVID-19 patients show distinct clinical features, and in some cases, during the severe stage of the condition, the disease severity leads to an acute respiratory disorder. In spite of several pieces of research in this area, the molecular mechanisms behind the development of disease severity are still not clearly understood. Recent studies demonstrated that SARS-CoV-2 alters the host cell splicing and transcriptional response to overcome the host immune response that provides the virus with favorable conditions to replicate efficiently within the host cells. In several disease conditions, aberrant splicing could lead to the development of novel chimeric transcripts that could promote the functional alternations of the cell. As severe SARS-CoV-2 infection was reported to cause abnormal splicing in the infected cells, we could expect the generation and expression of novel chimeric transcripts. However, no study so far has attempted to check whether novel chimeric transcripts are expressed in severe SARS-CoV-2 infections. In this study, we analyzed several publicly available blood transcriptome datasets of severe COVID-19, mild COVID-19, other severe respiratory viral infected patients, and healthy individuals. We identified 424 severe COVID-19 -specific chimeric transcripts, 42 of which were recurrent. Further, we detected 189 chimeric transcripts common to severe COVID-19 and multiple severe respiratory viral infections. Pathway and gene enrichment analysis of the parental genes of these two subsets of chimeric transcripts reveals that these are potentially involved in immune-related processes, interferon signaling, and inflammatory responses, which signify their potential association with immune dysfunction leading to the development of disease severity. Our study provides the first detailed expression landscape of chimeric transcripts in severe COVID-19 and other severe respiratory viral infections.

Targets of Immune Escape Mechanisms in Cancer: Basis for Development and Evolution of Cancer Immune Checkpoint Inhibitors.

Immune checkpoint blockade (ICB) has emerged as a novel therapeutic tool for cancer therapy in the last decade. Unfortunately, a small number of patients benefit from approved immune checkpoint inhibitors (ICIs). Therefore, multiple studies are being conducted to find new ICIs and combination strategies to improve the current ICIs. In this review, we discuss some approved immune checkpoints, such as PD-L1, PD-1, and CTLA-4, and also highlight newer emerging ICIs. For instance, HLA-E, overexpressed by tumor cells, represents an immune-suppressive feature by binding CD94/NKG2A, on NK and T cells. NKG2A blockade recruits CD8+ T cells and activates NK cells to decrease the tumor burden. NKG2D acts as an NK cell activating receptor that can also be a potential ICI. The adenosine A2A and A2B receptors, CD47-SIRPα, TIM-3, LAG-3, TIGIT, and VISTA are targets that also contribute to cancer immunoresistance and have been considered for clinical trials. Their antitumor immunosuppressive functions can be used to develop blocking antibodies. PARPs, mARTs, and B7-H3 are also other potential targets for immunosuppression. Additionally, miRNA, mRNA, and CRISPR-Cas9-mediated immunotherapeutic approaches are being investigated with great interest. Pre-clinical and clinical studies project these targets as potential immunotherapeutic candidates in different cancer types for their robust antitumor modulation.

Functional and regulatory impact of chimeric RNAs in human normal and cancer cells.

Fusions of two genes can lead to the generation of chimeric RNAs, which may have a distinct functional role from their original molecules. Chimeric RNAs could encode novel functional proteins or serve as novel long noncoding RNAs (lncRNAs). The appearance of chimeric RNAs in a cell could help to generate new functionality and phenotypic diversity that might facilitate this cell to survive against new environmental stress. Several recent studies have demonstrated the functional roles of various chimeric RNAs in cancer progression and are considered as biomarkers for cancer diagnosis and sometimes even drug targets. Further, the growing evidence demonstrated the potential functional association of chimeric RNAs with cancer heterogeneity and drug resistance cancer evolution. Recent studies highlighted that chimeric RNAs also have functional potentiality in normal physiological processes. Several functionally potential chimeric RNAs were discovered in human cancer and normal cells in the last two decades. This could indicate that chimeric RNAs are the hidden layer of the human transcriptome that should be explored from the functional insights to better understand the functional evolution of the genome and disease development that could facilitate clinical practice improvements. This review summarizes the current knowledge of chimeric RNAs and highlights their functional, regulatory, and evolutionary impact on different cancers and normal physiological processes. Further, we will discuss the potential functional roles of a recently discovered novel class of chimeric RNAs named sense-antisense/cross-strand chimeric RNAs generated by the fusion of the bi-directional transcripts of the same gene. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

Activation of the Plasmodium egress effector subtilisin-like protease 1 is achieved by plasmepsin X destruction of the propiece.

Following each round of replication, daughter merozoites of the malaria parasite Plasmodium falciparum escape (egress) from the infected host red blood cell (RBC) by rupturing the parasitophorous vacuole membrane (PVM) and the RBC membrane (RBCM). A proteolytic cascade orchestrated by the parasite’s serine protease, subtilisin-like protease 1 (SUB1) regulates the membrane breakdown. SUB1 activation involves primary auto-processing of the 82 kDa zymogen to a 54 kDa (p54) intermediate that remains bound to its inhibitory propiece (p31) post cleavage. A second processing step converts p54 to the terminal 47 kDa (p47) form of SUB1. Although the aspartic protease plasmepsin X (PM X) has been implicated in the activation of SUB1, the mechanism remains unknown. Here, we show that upon knockdown of PM X the inhibitory p31/p54 complex of SUB1 accumulates in the parasites. Using recombinant PM X and SUB1, we show that PM X can directly cleave both p31 and p54. We have mapped the cleavage sites on recombinant p31. Furthermore, we demonstrate that the conversion of p54 to p47 can be effected by cleavage at either a SUB1 or PM X cleavage site that are adjacent to one another. Importantly once the p31 is removed, p54 is fully functional inside the parasites suggesting that the conversion to p47 is dispensable for SUB1 activity. Relief of propiece inhibition via a heterologous protease is a novel mechanism for subtilisin activation. Significance Statement: Malaria parasites replicate inside a parasitophorous vacuole within the host red blood cells. Exit of mature progeny from the infected host cells is essential for further dissemination. Parasite exit is a highly regulated, explosive process that involves membrane breakdown. To do this, the parasite utilizes a serine protease, called the subtilisin-like protease 1 or SUB1 that proteolytically activates various effector proteins. SUB1 activity is dependent on an upstream protease, called plasmepsin X (PM X), although the mechanism was unknown. Here we describe the molecular basis for PM X mediated SUB1 activation. PM X proteolytically degrades the inhibitory segment of SUB1, thereby activating it. Involvement of a heterologous protease is a novel mechanism for subtilisin activation.

The landscape of differential splicing and transcript alternations in severe COVID-19 infection.

Viral infections can modulate the widespread alternations of cellular splicing, favouring viral replication within the host cells by overcoming host immune responses. However, how SARS-CoV-2 induces host cell differential splicing and affects the landscape of transcript alternation in severe COVID-19 infection remains elusive. Understanding the differential splicing and transcript alternations in severe COVID-19 infection may improve our molecular insights into the SARS-CoV-2 pathogenesis. In this study, we analysed the publicly available blood and lung transcriptome data of severe COVID-19 patients, blood transcriptome data of recovered COVID-19 patients at 12-, 16- and 24-week postinfection and healthy controls. We identified a significant transcript isoform switching in the individual blood and lung RNA-seq data of severe COVID-19-infected patients and 25 common genes that alter their transcript isoform in both blood and lung samples. Altered transcripts show significant loss of the open reading frame, functional domains and switch from coding to noncoding transcript, impacting normal cellular functions. Furthermore, we identified the expression of several novel recurrent chimeric transcripts in the blood samples from severe COVID-19 patients. Moreover, the analysis of the isoform switching into blood samples from recovered COVID-19 patients highlights that there is no significant isoform switching in 16- and 24-week postinfection, and the levels of expressed chimeric transcripts are reduced. This finding emphasizes that SARS-CoV-2 severe infection induces widespread splicing in the host cells, which could help the virus alter the host immune responses and facilitate the viral replication within the host and the efficient translation of viral proteins.

Identifying long-term effects of SARS-CoV-2 and their association with social determinants of health in a cohort of over one million COVID-19 survivors.

BACKGROUND: Despite an abundance of information on the risk factors of SARS-CoV-2, there have been few US-wide studies of long-term effects. In this paper we analyzed a large medical claims database of US based individuals to identify common long-term effects as well as their associations with various social and medical risk factors. METHODS: The medical claims database was obtained from a prominent US based claims data processing company, namely Change Healthcare. In addition to the claims data, the dataset also consisted of various social determinants of health such as race, income, education level and veteran status of the individuals. A self-controlled cohort design (SCCD) observational study was performed to identify ICD-10 codes whose proportion was significantly increased in the outcome period compared to the control period to identify significant long-term effects. A logistic regression-based association analysis was then performed between identified long-term effects and social determinants of health. RESULTS: Among the over 1.37 million COVID patients in our datasets we found 36 out of 1724 3-digit ICD-10 codes to be statistically significantly increased in the post-COVID period (p-value < 0.05). We also found one combination of ICD-10 codes, corresponding to 'other anemias' and 'hypertension', that was statistically significantly increased in the post-COVID period (p-value < 0.05). Our logistic regression-based association analysis with social determinants of health variables, after adjusting for comorbidities and prior conditions, showed that age and gender were significantly associated with the multiple long-term effects. Race was only associated with 'other sepsis', income was only associated with 'Alopecia areata' (autoimmune disease causing hair loss), while education level was only associated with 'Maternal infectious and parasitic diseases' (p-value < 0.05). CONCLUSION: We identified several long-term effects of SARS-CoV-2 through a self-controlled study on a cohort of over one million patients. Furthermore, we found that while age and gender are commonly associated with the long-term effects, other social determinants of health such as race, income and education levels have rare or no significant associations.

The Risk of Hospitalization and Mortality After Breakthrough SARS-CoV-2 Infection by Vaccine Type: Observational Study of Medical Claims Data.

BACKGROUND: Several risk factors have been identified for severe COVID-19 disease by the scientific community. In this paper, we focus on understanding the risks for severe COVID-19 infections after vaccination (ie, in breakthrough SARS-CoV-2 infections). Studying these risks by vaccine type, age, sex, comorbidities, and any prior SARS-CoV-2 infection is important to policy makers planning further vaccination efforts. OBJECTIVE: We performed a comparative study of the risks of hospitalization (n=1140) and mortality (n=159) in a SARS-CoV-2 positive cohort of 19,815 patients who were all fully vaccinated with the Pfizer, Moderna, or Janssen vaccines. METHODS: We performed Cox regression analysis to calculate the risk factors for developing a severe breakthrough SARS-CoV-2 infection in the study cohort by controlling for vaccine type, age, sex, comorbidities, and a prior SARS-CoV-2 infection. RESULTS: We found lower hazard ratios for those receiving the Moderna vaccine (P<.001) and Pfizer vaccine (P<.001), with the lowest hazard rates being for Moderna, as compared to those who received the Janssen vaccine, independent of age, sex, comorbidities, vaccine type, and prior SARS-CoV-2 infection. Further, individuals who had a SARS-CoV-2 infection prior to vaccination had some increased protection over and above the protection already provided by the vaccines, from hospitalization (P=.001) and death (P=.04), independent of age, sex, comorbidities, and vaccine type. We found that the top statistically significant risk factors for severe breakthrough SARS-CoV-2 infections were age of >50, male gender, moderate and severe renal failure, severe liver disease, leukemia, chronic lung disease, coagulopathy, and alcohol abuse. CONCLUSIONS: Among individuals who were fully vaccinated, the risk of severe breakthrough SARS-CoV-2 infection was lower for recipients of the Moderna or Pfizer vaccines and higher for recipients of the Janssen vaccine. These results from our analysis at a population level will be helpful to public health policy makers. Our result on the influence of a previous SARS-CoV-2 infection necessitates further research into the impact of multiple exposures on the risk of developing severe COVID-19.

Identifying Hub Genes Associated with Neoadjuvant Chemotherapy Resistance in Breast Cancer and Potential Drug Repurposing for the Development of Precision Medicine.

Breast cancer is the second leading cause of morbidity and mortality in women worldwide. Despite advancements in the clinical application of neoadjuvant chemotherapy (NAC), drug resistance remains a major concern hindering treatment efficacy. Thus, identifying the key genes involved in driving NAC resistance and targeting them with known potential FDA-approved drugs could be applied to advance the precision medicine strategy. With this aim, we performed an integrative bioinformatics study to identify the key genes associated with NAC resistance in breast cancer and then performed the drug repurposing to identify the potential drugs which could use in combination with NAC to overcome drug resistance. In this study, we used publicly available RNA-seq datasets from the samples of breast cancer patients sensitive and resistant to chemotherapy and identified a total of 1446 differentially expressed genes in NAC-resistant breast cancer patients. Next, we performed gene co-expression network analysis to identify significantly co-expressed gene modules, followed by MCC (Multiple Correlation Clustering) clustering algorithms and identified 33 key hub genes associated with NAC resistance. mRNA-miRNA network analysis highlighted the potential impact of these hub genes in altering the regulatory network in NAC-resistance breast cancer cells. Further, several hub genes were found to be significantly involved in the poor overall survival of breast cancer patients. Finally, we identified FDA-approved drugs which could be useful for potential drug repurposing against those hub genes. Altogether, our findings provide new insight into the molecular mechanisms of NAC resistance and pave the way for drug repurposing techniques and personalized treatment to overcome NAC resistance in breast cancer.

Maturation and substrate processing topography of the Plasmodium falciparum invasion/egress protease plasmepsin X.

The malaria parasite Plasmodium invades a host erythrocyte, multiplies within a parasitophorous vacuole (PV) and then ruptures the PV and erythrocyte membranes in a process known as egress. Both egress and invasion are controlled by effector proteins discharged from specialized secretory organelles. The aspartic protease plasmepsin X (PM X) regulates activity for many of these effectors, but it is unclear how PM X accesses its diverse substrates that reside in different organelles. PM X also autoprocesses to generate different isoforms. The function of this processing is not understood. We have mapped the self-cleavage sites and have constructed parasites with cleavage site mutations. Surprisingly, a quadruple mutant that remains full-length retains in vitro activity, is trafficked normally, and supports normal egress, invasion and parasite growth. The N-terminal half of the prodomain stays bound to the catalytic domain even after processing and is required for proper intracellular trafficking of PM X. We find that this enzyme cleaves microneme and exoneme substrates before discharge, while the rhoptry substrates that are dependent on PM X activity are cleaved after exoneme discharge into the PV. The data give insight into the temporal, spatial and biochemical control of this unusual but important aspartic protease.

The nepenthesin insert in the Plasmodium falciparum aspartic protease plasmepsin V is necessary for enzyme function.

Plasmepsin V (PM V) is a pepsin-like aspartic protease essential for growth of the malarial parasite Plasmodium falciparum. Previous work has shown PM V to be an endoplasmic reticulum-resident protease that processes parasite proteins destined for export into the host cell. Depletion or inhibition of the enzyme is lethal during asexual replication within red blood cells as well as during the formation of sexual stage gametocytes. The structure of the Plasmodium vivax PM V has been characterized by X-ray crystallography, revealing a canonical pepsin fold punctuated by structural features uncommon to secretory aspartic proteases; however, the function of this unique structure is unclear. Here, we used parasite genetics to probe these structural features by attempting to rescue lethal PM V depletion with various mutant enzymes. We found an unusual nepenthesin 1-type insert in the PM V gene to be essential for parasite growth and PM V activity. Mutagenesis of the nepenthesin insert suggests that both its amino acid sequence and one of the two disulfide bonds that undergird its structure are required for the insert's role in PM V function. Furthermore, molecular dynamics simulations paired with Markov state modeling suggest that mutations to the nepenthesin insert may allosterically affect PM V catalysis through multiple mechanisms. Taken together, these data provide further insights into the structure of the P. falciparum PM V protease.