Hijacking a rapid and scalable metagenomic method reveals subgenome dynamics and evolution in polyploid plants.

Premise: The genomes of polyploid plants archive the evolutionary events leading to their present forms. However, plant polyploid genomes present numerous hurdles to the genome comparison algorithms for classification of polyploid types and exploring genome dynamics. Methods: Here, the problem of intra- and inter-genome comparison for examining polyploid genomes is reframed as a metagenomic problem, enabling the use of the rapid and scalable MinHashing approach. To determine how types of polyploidy are described by this metagenomic approach, plant genomes were examined from across the polyploid spectrum for both k-mer composition and frequency with a range of k-mer sizes. In this approach, no subgenome-specific k-mers are identified; rather, whole-chromosome k-mer subspaces were utilized. Results: Given chromosome-scale genome assemblies with sufficient subgenome-specific repetitive element content, literature-verified subgenomic and genomic evolutionary relationships were revealed, including distinguishing auto- from allopolyploidy and putative progenitor genome assignment. The sequences responsible were the rapidly evolving landscape of transposable elements. An investigation into the MinHashing parameters revealed that the downsampled k-mer space (genomic signatures) produced excellent approximations of sequence similarity. Furthermore, the clustering approach used for comparison of the genomic signatures is scrutinized to ensure applicability of the metagenomics-based method. Discussion: The easily implementable and highly computationally efficient MinHashing-based sequence comparison strategy enables comparative subgenomics and genomics for large and complex polyploid plant genomes. Such comparisons provide evidence for polyploidy-type subgenomic assignments. In cases where subgenome-specific repeat signal may not be adequate given a chromosomes' global k-mer profile, alternative methods that are more specific but more computationally complex outperform this approach.

Middle East Respiratory Syndrome Coronavirus Could be a Priority Pathogen to Cause Public Health Emergency: Noticeable Features and Counteractive Measures.

Middle East respiratory syndrome (MERS) is caused by a specific strain of the 6 types of human coronaviruses (HCoV). MERS-CoV has spread unchecked since it was first discovered in Saudi Arabia in 2012. The virus most likely spreads through nosocomial and zoonotic channels. Genetic analyses suggest that bats were the initial hosts and that the disease spread to camels. Person-to-person transmission occurs with varying frequency, being most prevalent in clinical settings and the least common among the general population and among close relatives. Due to the severity of the illness, high fatality rate, potential for epidemic spread, and lack of adequate medical countermeasures, the World Health Organization (WHO) continues to list MERS-CoV as a priority pathogen. While no specific antiviral medicines exist, a combination of antivirals has shown promise in recent clinical trials. Vaccines against MERS-CoV are critically needed and are currently being developed. Early diagnosis and implementing appropriate infection control measures are keys to preventing hospital-associated outbreaks. Preventive measures include avoiding raw or undercooked meats and other animal products, ensuring proper hand hygiene in healthcare settings and around dromedaries, educating the public and healthcare personnel about the disease, and adhering to other recommended practices. Countries with a high prevalence of MERS should adhere to regulations designed to limit the transmission of the virus. The recent spread of MERS-CoV highlights the importance of public awareness regarding the significance of reporting symptoms so that appropriate control measures can be adopted. The narrative review discusses the incidence of MERS, its clinical presentation, potential transmission routes, recent reports, preventative and control measures, and current therapeutic options.

Fairy: fast approximate coverage for multi-sample metagenomic binning.

BACKGROUND: Metagenomic binning, the clustering of assembled contigs that belong to the same genome, is a crucial step for recovering metagenome-assembled genomes (MAGs). Contigs are linked by exploiting consistent signatures along a genome, such as read coverage patterns. Using coverage from multiple samples leads to higher-quality MAGs; however, standard pipelines require all-to-all read alignments for multiple samples to compute coverage, becoming a key computational bottleneck. RESULTS: We present fairy ( https://github.com/bluenote-1577/fairy ), an approximate coverage calculation method for metagenomic binning. Fairy is a fast k-mer-based alignment-free method. For multi-sample binning, fairy can be > 250 × faster than read alignment and accurate enough for binning. Fairy is compatible with several existing binners on host and non-host-associated datasets. Using MetaBAT2, fairy recovers 98.5 % of MAGs with > 50 % completeness and < 5 % contamination relative to alignment with BWA. Notably, multi-sample binning with fairy is always better than single-sample binning using BWA ( > 1.5 × more > 50 % complete MAGs on average) while still being faster. For a public sediment metagenome project, we demonstrate that multi-sample binning recovers higher quality Asgard archaea MAGs than single-sample binning and that fairy's results are indistinguishable from read alignment. CONCLUSIONS: Fairy is a new tool for approximately and quickly calculating multi-sample coverage for binning, resolving a computational bottleneck for metagenomics. Video Abstract.

Malivhu: A Comprehensive Bioinformatics Resource for Filtering SARS and MERS Virus Proteins by Their Classification, Family and Species, and Prediction of Their Interactions Against Human Proteins.

COVID 19 pandemic is still ongoing, having taken more than 6 million human lives with it, and it seems that the world will have to learn how to live with the virus around. In consequence, there is a need to develop different treatments against it, not only with vaccines, but also new medicines. To do this, human-virus protein-protein interactions (PPIs) play a key part in drug-target discovery, but finding them experimentally can be either costly or sometimes unreliable. Therefore, computational methods arose as a powerful alternative to predict these interactions, reducing costs and helping researchers confirm only certain interactions instead of trying all possible combinations in the laboratory. Malivhu is a tool that predicts human-virus PPIs through a 4-phase process using machine learning models, where phase 1 filters ssRNA(+) class virus proteins, phase 2 filters Coronaviridae family proteins and phase 3 filters severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) species proteins, and phase 4 predicts human-SARS-CoV/SARS-CoV-2/MERS protein-protein interactions. The performance of the models was measured with Matthews correlation coefficient, F1-score, specificity, sensitivity, and accuracy scores, getting accuracies of 99.07%, 99.83%, and 100% for the first 3 phases, respectively, and 94.24% for human-SARS-CoV PPI, 94.50% for human-SARS-CoV-2 PPI, and 95.45% for human-MERS PPI on independent testing. All the prediction models developed for each of the 4 phases were implemented as web server which is freely available at https://kaabil.net/malivhu/.

Structural basis of main proteases of MERS-CoV bound to antineoplastic drug carmofur.

Recurrent epidemics of coronaviruses have posed significant threats to human life and health. The mortality rate of patients infected with the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is 35 %. The main protease (Mpro) plays a crucial role in the MERS-CoV life cycle, and Mpro exhibited a high degree of conservation among different coronaviruses. Therefore inhibition of Mpro has become an effective strategy for the development of broad-spectrum anti-coronaviral drugs. The inhibition of SARS-CoV-2 Mpro by the anti-tumor drug carmofur has been revealed, but structural studies of carmofur in complex with Mpro from other types of coronavirus have not been reported. Hence, we revealed the structure of the MERS-CoV Mpro-carmofur complex, analysed the structural basis for the binding of carmofur to MERS-CoV Mpro in detail, and compared the binding patterns of carmofur to Mpros of two different coronaviruses, MERS-CoV and SARS-CoV-2. Considering the importance of Mpros for coronavirus therapy, structural understanding of Mpro inhibition by carmofur could contribute to the design and development of novel antiviral drugs with safe and broad-spectrum efficacy.

Mathematical assessment of control strategies against the spread of MERS-CoV in humans and camels in Saudi Arabia.

A new mathematical model for the transmission dynamics and control of the Middle Eastern respiratory syndrome (MERS), a respiratory virus caused by MERS-CoV coronavirus (and primarily spread to humans by dromedary camels) that first emerged out of the Kingdom of Saudi Arabia (KSA) in 2012, was designed and used to study the transmission dynamics of the disease in a human-camel population within the KSA. Rigorous analysis of the model, which was fitted and cross-validated using the observed MERS-CoV data for the KSA, showed that its disease-free equilibrium was locally asymptotically stable whenever its reproduction number (denoted by $ {\mathbb R}_{0M} $) was less than unity. Using the fixed and estimated parameters of the model, the value of $ {\mathbb R}_{0M} $ for the KSA was estimated to be 0.84, suggesting that the prospects for MERS-CoV elimination are highly promising. The model was extended to allow for the assessment of public health intervention strategies, notably the potential use of vaccines for both humans and camels and the use of face masks by humans in public or when in close proximity with camels. Simulations of the extended model showed that the use of the face mask by humans who come in close proximity with camels, as a sole public health intervention strategy, significantly reduced human-to-camel and camel-to-human transmission of the disease, and this reduction depends on the efficacy and coverage of the mask type used in the community. For instance, if surgical masks are prioritized, the disease can be eliminated in both the human and camel population if at least 45% of individuals who have close contact with camels wear them consistently. The simulations further showed that while vaccinating humans as a sole intervention strategy only had marginal impact in reducing the disease burden in the human population, an intervention strategy based on vaccinating camels only resulted in a significant reduction in the disease burden in camels (and, consequently, in humans as well). Thus, this study suggests that attention should be focused on effectively combating the disease in the camel population, rather than in the human population. Furthermore, the extended model was used to simulate a hybrid strategy, which combined vaccination of both humans and camels as well as the use of face masks by humans. This simulation showed a marked reduction of the disease burden in both humans and camels, with an increasing effectiveness level of this intervention, in comparison to the baseline scenario or any of the aforementioned sole vaccination scenarios. In summary, this study showed that the prospect of the elimination of MERS-CoV-2 in the Kingdom of Saudi Arabia is promising using pharmaceutical (vaccination) and nonpharmaceutical (mask) intervention strategies, implemented in isolation or (preferably) in combination, that are focused on reducing the disease burden in the camel population.

Saudi Arabia's Middle East respiratory syndrome Coronavirus (MERS-CoV) outbreak: consequences, reactions, and takeaways.

Background: Middle East respiratory syndrome (MERS) is a viral illness caused by the MERS-Coronavirus (MERS-CoV) that was first identified in Saudi Arabia in 2012. Saudi Arabia has reported most global MERS-CoV cases and deaths, with periodic outbreaks in other countries. Objectives: This review aims to provide a comprehensive overview of the 2023 MERS-CoV outbreak in Saudi Arabia, including its epidemiology, public health response, impact, and lessons learned. Methodology: This study utilized a narrative review approach, drawing on published literature and data from sources such as the WHO and the Centers for Disease Control and Prevention. Results: The 2023 outbreak was centered in the Riyadh region, with 312 confirmed cases and 97 deaths reported. MERS-CoV primarily spreads from dromedary camels to humans, with human-to-human transmission, especially in healthcare settings. The outbreak exhibited seasonal and spatial trends, with most cases during camel calving season and in rural areas with high camel populations. The Saudi Ministry of Health implemented a multi-faceted response, including enhancing surveillance, improving infection prevention, providing clinical support, and conducting risk communication. Over time, the response showed a decline in the number of cases and deaths, indicating its effectiveness. Conclusion: The outbreak has significant public health, economic, and social impacts, underscoring the ongoing threat of emerging zoonotic diseases. Key lessons include early case detection, efficient infection control, vaccine and treatment development, public engagement, and strengthening of regional and global collaboration to mitigate future outbreaks and safeguard public health.

StrainR2 accurately deconvolutes strain-level abundances in synthetic microbial communities.

Background: Synthetic microbial communities offer an opportunity to conduct reductionist research in tractable model systems. However, deriving abundances of highly related strains within these communities is currently unreliable. 16S rRNA gene sequencing does not resolve abundance at the strain level, standard methods for analysis of shotgun metagenomic sequencing do not account for ambiguous mapping between closely related strains, and other methods such as quantitative PCR (qPCR) scale poorly and are resource prohibitive for complex communities. We present StrainR2, which utilizes shotgun metagenomic sequencing paired with a k-mer-based normalization strategy to provide high accuracy strain-level abundances for all members of a synthetic community, provided their genomes. Results: Both in silico, and using sequencing data derived from gnotobiotic mice colonized with a synthetic fecal microbiota, StrainR2 resolves strain abundances with greater accuracy than other tools utilizing shotgun metagenomic sequencing reads and can resolve complex mixtures of highly related strains. Through experimental validation and benchmarking, we demonstrate that StrainR2's accuracy is comparable to that of qPCR on a subset of strains resolved using absolute quantification. Further, it is capable of scaling to communities of hundreds of strains and efficiently utilizes memory being capable of running both on personal computers and high-performance computing nodes. Conclusions: Using shotgun metagenomic sequencing reads is a viable method for determining accurate strain-level abundances in synthetic communities using StrainR2.

GWarrange: a pre- and post- genome-wide association studies pipeline for detecting phenotype-associated genome rearrangement events.

The use of k-mers to capture genetic variation in bacterial genome-wide association studies (bGWAS) has demonstrated its effectiveness in overcoming the plasticity of bacterial genomes by providing a comprehensive array of genetic variants in a genome set that is not confined to a single reference genome. However, little attempt has been made to interpret k-mers in the context of genome rearrangements, partly due to challenges in the exhaustive and high-throughput identification of genome structure and individual rearrangement events. Here, we present GWarrange, a pre- and post-bGWAS processing methodology that leverages the unique properties of k-mers to facilitate bGWAS for genome rearrangements. Repeat sequences are common instigators of genome rearrangements through intragenomic homologous recombination, and they are commonly found at rearrangement boundaries. Using whole-genome sequences, repeat sequences are replaced by short placeholder sequences, allowing the regions flanking repeats to be incorporated into relatively short k-mers. Then, locations of flanking regions in significant k-mers are mapped back to complete genome sequences to visualise genome rearrangements. Four case studies based on two bacterial species (Bordetella pertussis and Enterococcus faecium) and a simulated genome set are presented to demonstrate the ability to identify phenotype-associated rearrangements. GWarrange is available at https://github.com/DorothyTamYiLing/GWarrange.

Novel Pan-Coronavirus 3CL Protease Inhibitor MK-7845: Biological and Pharmacological Profiling.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to be a global threat due to its ability to evolve and generate new subvariants, leading to new waves of infection. Additionally, other coronaviruses like Middle East respiratory syndrome coronavirus (MERS-CoV, formerly known as hCoV-EMC), which first emerged in 2012, persist and continue to present a threat of severe illness to humans. The continued identification of novel coronaviruses, coupled with the potential for genetic recombination between different strains, raises the possibility of new coronavirus clades of global concern emerging. As a result, there is a pressing need for pan-CoV therapeutic drugs and vaccines. After the extensive optimization of an HCV protease inhibitor screening hit, a novel 3CLPro inhibitor (MK-7845) was discovered and subsequently profiled. MK-7845 exhibited nanomolar in vitro potency with broad spectrum activity against a panel of clinical SARS-CoV-2 subvariants and MERS-CoV. Furthermore, when administered orally, MK-7845 demonstrated a notable reduction in viral burdens by >6 log orders in the lungs of transgenic mice infected with SARS-CoV-2 (K18-hACE2 mice) and MERS-CoV (K18-hDDP4 mice).

Coexisting Sacrococcygeal Teratoma With Mild Encephalitis/Encephalopathy With a Reversible Splenial Lesion: A Case Report.

Mild encephalitis/encephalopathy with a reversible splenial lesion (MERS) is a rare disease characterized by a reversible lesion in the splenium of the corpus callosum (SCC) observed on MRI. The exact etiology of MERS is unknown, although infections and antiepileptic drugs have been reported as potential causes. Herein, we present the case of a 56-year-old male patient who experienced fever and headache for 3 days. He was referred to our hospital after symptomatic treatment by his primary care physician failed to improve his symptoms. The patient had no psychiatric symptoms or significant neurological findings. Head MRI revealed a high signal on SCC on diffusion-weighted imaging, raising the suspicion of MERS. All examinations to determine the cause of MERS were negative. The patient's symptoms improved with antibiotics and B complex vitamins. Upon admission, abdominal CT incidentally revealed a well-defined mass on the dorsal surface of the rectum suspected to be a tailgut cyst, warranting surgical resection. The cranial margin of the tumor was caudal to the third sacrum, and a trans-sacral approach was used for resection. The fifth sacrum and the coccyx were resected, and the tumor was resected without damaging the rectum. A histopathological examination revealed a mature teratoma without any malignancy. A follow-up CT at four months postoperatively showed no evidence of clinical recurrence of MERS. Adult-onset MERS is relatively rare, and no association with tumors has been reported. The association between encephalitis and teratomas includes ovarian teratomas, which cause anti-N-methyl-D-aspartate receptor encephalitis and paraneoplastic limbic encephalitis. Although the cause of MERS was unknown in this case, we report the coexistence of a sacral teratoma and MERS to contribute to the knowledge of the association between them.

Circulation of Non-Middle East Respiratory Syndrome (MERS) Coronaviruses in Imported Camels in Saudi Arabia.

Background Coronaviruses (CoVs) pose significant health risks to humans, with recent outbreaks like severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underscoring their zoonotic potential. Dromedary camels (Camelus dromedarius) have been implicated as intermediate hosts for MERS-CoV, prompting heightened surveillance efforts. This study aims to identify non-MERS-CoV CoVs in imported camels at the Jeddah seaport, Saudi Arabia, using molecular techniques. Methods Camel nasal swabs (n = 337) were collected from imported dromedary camels arriving at the Jeddah Islamic seaport from Sudan and Djibouti. Samples were tested for CoVs using real-time real-time reverse transcription polymerase chain reaction (RT-PCR) targeting the RNA-dependent RNA polymerase gene. Positive samples were confirmed by conventional RT-PCR and Sanger sequencing. Selected samples underwent RNA sequencing to identify viral genomes. The study underscores the importance of molecular surveillance in camels to mitigate zoonotic risks. Results Out of 337 camel samples tested, 28 (8.30%) were positive for CoVs, predominantly from camels imported from Djibouti, compared to Sudan (13.39% vs. 5.78%). Sequence analysis confirmed the presence of non-MERS CoVs, including camel alpha-coronavirus and human CoV-229E-related strains. These findings highlight potential viral diversity and transmission risks in imported camel populations. Conclusion This study identifies diverse CoVs circulating in imported dromedary camels at the Jeddah Islamic seaport, Saudi Arabia, underscoring their potential role in zoonotic transmission. Enhanced surveillance and collaborative efforts are essential to mitigate public health risks associated with novel coronavirus strains from camel populations.

Mapping immunodominant sites on the MERS-CoV spike glycoprotein targeted by infection-elicited antibodies in humans.

Middle East respiratory syndrome coronavirus (MERS-CoV) first emerged in 2012 and causes human infections in endemic regions. Vaccines and therapeutics in development against MERS-CoV focus on the spike (S) glycoprotein to prevent viral entry into target cells. These efforts are limited by a poor understanding of antibody responses elicited by infection. Here, we analyze S-directed antibody responses in plasma collected from MERS-CoV-infected individuals. We observe that binding and neutralizing antibodies peak 1-6 weeks after symptom onset/hospitalization, persist for at least 6 months, and neutralize human and camel MERS-CoV strains. We show that the MERS-CoV S1 subunit is immunodominant and that antibodies targeting S1, particularly the receptor-binding domain (RBD), account for most plasma neutralizing activity. Antigenic site mapping reveals that plasma antibodies frequently target RBD epitopes, whereas targeting of S2 subunit epitopes is rare. Our data reveal the humoral immune responses elicited by MERS-CoV infection, which will guide vaccine and therapeutic design.

Lessons learnt from broad-spectrum coronavirus antiviral drug discovery.

INTRODUCTION: Highly pathogenic coronaviruses (CoVs), such as severe acute respiratory syndrome CoV (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and the most recent SARS-CoV-2 responsible for the COVID-19 pandemic, pose significant threats to human populations over the past two decades. These CoVs have caused a broad spectrum of clinical manifestations ranging from asymptomatic to severe distress syndromes (ARDS), resulting in high morbidity and mortality. AREAS COVERED: The accelerated advancements in antiviral drug discovery, spurred by the COVID-19 pandemic, have shed new light on the imperative to develop treatments effective against a broad spectrum of CoVs. This perspective discusses strategies and lessons learnt in targeting viral non-structural proteins, structural proteins, drug repurposing, and combinational approaches for the development of antivirals against CoVs. EXPERT OPINION: Drawing lessons from the pandemic, it becomes evident that the absence of efficient broad-spectrum antiviral drugs increases the vulnerability of public health systems to the potential onslaught by highly pathogenic CoVs. The rapid and sustained spread of novel CoVs can have devastating consequences without effective and specifically targeted treatments. Prioritizing the effective development of broad-spectrum antivirals is imperative for bolstering the resilience of public health systems and mitigating the potential impact of future highly pathogenic CoVs.

Mild Encephalopathy/Encephalitis With Reversible Splenial Lesion Associated With Meningitis Related to Mumps Disease: An Unusual Presentation in a Male Adult.

Mild encephalitis/encephalopathy with reversible splenial lesion (MERS) is characterized by mild neurological manifestations associated with spontaneously reversible lesions of the splenium of the corpus callosum. While various conditions and diseases can trigger MERS, infectious causes predominate, with mumps being notably linked to MERS in the pediatric population. Although rare in adults, there are sporadic case reports associating mumps with MERS. Here we report a 23-year-old male patient with a typical presentation of mumps who presented with meningeal syndrome, dizziness, seizures, and right orchitis. Brain MRI showed classic findings of MERS syndrome while cerebrospinal fluid analysis demonstrated lymphocytic pleocytosis. Our patient had a confirmed diagnosis of mumps disease with multiple complications, including MERS, meningitis, and orchitis, and was managed with symptomatic medications and antiviral therapy. Subsequently, there was a gradual resolution of these manifestations and the outcome was favorable, with no residual sequelae.

The effectiveness of intervention measures on MERS-CoV transmission by using the contact networks reconstructed from link prediction data.

Introduction: Mitigating the spread of infectious diseases is of paramount concern for societal safety, necessitating the development of effective intervention measures. Epidemic simulation is widely used to evaluate the efficacy of such measures, but realistic simulation environments are crucial for meaningful insights. Despite the common use of contact-tracing data to construct realistic networks, they have inherent limitations. This study explores reconstructing simulation networks using link prediction methods as an alternative approach. Methods: The primary objective of this study is to assess the effectiveness of intervention measures on the reconstructed network, focusing on the 2015 MERS-CoV outbreak in South Korea. Contact-tracing data were acquired, and simulation networks were reconstructed using the graph autoencoder (GAE)-based link prediction method. A scale-free (SF) network was employed for comparison purposes. Epidemic simulations were conducted to evaluate three intervention strategies: Mass Quarantine (MQ), Isolation, and Isolation combined with Acquaintance Quarantine (AQ + Isolation). Results: Simulation results showed that AQ + Isolation was the most effective intervention on the GAE network, resulting in consistent epidemic curves due to high clustering coefficients. Conversely, MQ and AQ + Isolation were highly effective on the SF network, attributed to its low clustering coefficient and intervention sensitivity. Isolation alone exhibited reduced effectiveness. These findings emphasize the significant impact of network structure on intervention outcomes and suggest a potential overestimation of effectiveness in SF networks. Additionally, they highlight the complementary use of link prediction methods. Discussion: This innovative methodology provides inspiration for enhancing simulation environments in future endeavors. It also offers valuable insights for informing public health decision-making processes, emphasizing the importance of realistic simulation environments and the potential of link prediction methods.

A survey of k-mer methods and applications in bioinformatics.

The rapid progression of genomics and proteomics has been driven by the advent of advanced sequencing technologies, large, diverse, and readily available omics datasets, and the evolution of computational data processing capabilities. The vast amount of data generated by these advancements necessitates efficient algorithms to extract meaningful information. K-mers serve as a valuable tool when working with large sequencing datasets, offering several advantages in computational speed and memory efficiency and carrying the potential for intrinsic biological functionality. This review provides an overview of the methods, applications, and significance of k-mers in genomic and proteomic data analyses, as well as the utility of absent sequences, including nullomers and nullpeptides, in disease detection, vaccine development, therapeutics, and forensic science. Therefore, the review highlights the pivotal role of k-mers in addressing current genomic and proteomic problems and underscores their potential for future breakthroughs in research.

Mild encephalitis/encephalopathy with a reversible splenial lesion (MERS).

Background: Mild encephalitis/encephalopathy with a reversible splenial lesion (MERS) is increasingly recognized as a clinicoradiological syndrome. Its etiology is diverse, encompassing a variety of triggers, including infections and metabolic abnormalities. Uniquely, MERS may present with psychiatric symptoms, such as delirium, visual hallucinations, and catatonia, posing diagnostic challenges. The variability of these neuropsychiatric symptoms necessitates early diagnosis through magnetic resonance imaging (MRI) to avoid prolonged antipsychotic treatment. Case Presentation: This report details a case of MERS in a 39-year-old male. The patient initially presented with headache, sore throat, and abnormal laboratory results: leukocytosis, neutrophilia with a left shift, elevated C-reactive protein (CRP) levels, and hyponatremia. On the fourth day of admission, he developed severe anxiety and restlessness, exhibited thoughts of death, and reported experiencing vivid hallucinations upon closing his eyes. MRI revealed a hyperintense lesion in the corpus callosum. A lumbar puncture showed no increase in cell count or protein. The patient showed a positive response to treatment with antibiotics and olanzapine, demonstrating rapid symptomatic improvement. A follow-up MRI on the 11th day showed complete resolution of the brain lesions. Six months later, no neurological or psychiatric sequelae were noted. The patient's clinical progression and imaging findings led to a definitive diagnosis of MERS. Conclusion: The early presentation of symptoms such as restlessness, hallucinations, and death ideation played a critical role in diagnosing MERS, with early MRI examination being instrumental in both diagnosis and preventing prolonged antipsychotic medication use.

Human cytokine and coronavirus nucleocapsid protein interactivity using large-scale virtual screens.

Understanding the interactions between SARS-CoV-2 and the human immune system is paramount to the characterization of novel variants as the virus co-evolves with the human host. In this study, we employed state-of-the-art molecular docking tools to conduct large-scale virtual screens, predicting the binding affinities between 64 human cytokines against 17 nucleocapsid proteins from six betacoronaviruses. Our comprehensive in silico analyses reveal specific changes in cytokine-nucleocapsid protein interactions, shedding light on potential modulators of the host immune response during infection. These findings offer valuable insights into the molecular mechanisms underlying viral pathogenesis and may guide the future development of targeted interventions. This manuscript serves as insight into the comparison of deep learning based AlphaFold2-Multimer and the semi-physicochemical based HADDOCK for protein-protein docking. We show the two methods are complementary in their predictive capabilities. We also introduce a novel algorithm for rapidly assessing the binding interface of protein-protein docks using graph edit distance: graph-based interface residue assessment function (GIRAF). The high-performance computational framework presented here will not only aid in accelerating the discovery of effective interventions against emerging viral threats, but extend to other applications of high throughput protein-protein screens.

Developments in treatment for middle east respiratory syndrome coronavirus (MERS-CoV).

INTRODUCTION: An important respiratory pathogen that has led to multiple hospital outbreaks both inside and outside of the Arabian Peninsula is the Middle East Respiratory Syndrome Coronavirus (MERS-CoV). Given the elevated case fatality rate, there exists a pressing requirement for efficacious therapeutic agents. AREAS COVERED: This is an updated review of the developments in MERS treatment approaches. Using databases like PubMed, Embase, Cochrane, Scopus, and Google Scholar, a thorough search was carried out utilizing keywords like 'MERS,' 'MERS-CoV,' and 'Middle East respiratory syndrome' in conjunction with 'treatment' or 'therapy' from Jan 2012 to Feb 2024. EXPERT OPINION: MERS-CoV is a highly pathogenic respiratory infection that emerged in 2012 and continues to pose a significant public health threat. Despite ongoing efforts to control the spread of MERS-CoV, there is currently no specific antiviral treatment available. While many agents have been tested both in vivo and in vitro, none of them have been thoroughly examined in extensive clinical trials. Only case reports, case series, or cohort studies have been made available as clinical studies. However, there is a limited number of randomized-controlled trials. Because cases are irregular and sporadic, conducting a large prospective randomized trials for establishing an efficacious treatment might be difficult.