Extremely potent human monoclonal antibodies from COVID-19 convalescent patients.

Human monoclonal antibodies are safe, preventive, and therapeutic tools that can be rapidly developed to help restore the massive health and economic disruption caused by the coronavirus disease 2019 (COVID-19) pandemic. By single-cell sorting 4,277 SARS-CoV-2 spike protein-specific memory B cells from 14 COVID-19 survivors, 453 neutralizing antibodies were identified. The most potent neutralizing antibodies recognized the spike protein receptor-binding domain, followed in potency by antibodies that recognize the S1 domain, the spike protein trimer, and the S2 subunit. Only 1.4% of them neutralized the authentic virus with a potency of 1-10 ng/mL. The most potent monoclonal antibody, engineered to reduce the risk of antibody-dependent enhancement and prolong half-life, neutralized the authentic wild-type virus and emerging variants containing D614G, E484K, and N501Y substitutions. Prophylactic and therapeutic efficacy in the hamster model was observed at 0.25 and 4 mg/kg respectively in absence of Fc functions.

Hybrid immunity improves B cells and antibodies against SARS-CoV-2 variants.

The emergence of SARS-CoV-2 variants is jeopardizing the effectiveness of current vaccines and limiting the application of monoclonal antibody-based therapy for COVID-19 (refs. 1,2). Here we analysed the memory B cells of five naive and five convalescent people vaccinated with the BNT162b2 mRNA vaccine to investigate the nature of the B cell and antibody response at the single-cell level. Almost 6,000 cells were sorted, over 3,000 cells produced monoclonal antibodies against the spike protein and more than 400 cells neutralized the original SARS-CoV-2 virus first identified in Wuhan, China. The B.1.351 (Beta) and B.1.1.248 (Gamma) variants escaped almost 70% of these antibodies, while a much smaller portion was impacted by the B.1.1.7 (Alpha) and B.1.617.2 (Delta) variants. The overall loss of neutralization was always significantly higher in the antibodies from naive people. In part, this was due to the IGHV2-5;IGHJ4-1 germline, which was found only in people who were convalescent and generated potent and broadly neutralizing antibodies. Our data suggest that people who are seropositive following infection or primary vaccination will produce antibodies with increased potency and breadth and will be able to better control emerging SARS-CoV-2 variants.

Author Correction: Commensal-driven immune zonation of the liver promotes host defence.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03346-0.

Commensal-driven immune zonation of the liver promotes host defence.

The liver connects the intestinal portal vasculature with the general circulation, using a diverse array of immune cells to protect from pathogens that translocate from the gut1. In liver lobules, blood flows from portal triads that are situated in periportal lobular regions to the central vein via a polarized sinusoidal network. Despite this asymmetry, resident immune cells in the liver are considered to be broadly dispersed across the lobule. This differs from lymphoid organs, in which immune cells adopt spatially biased positions to promote effective host defence2,3. Here we used quantitative multiplex imaging, genetic perturbations, transcriptomics, infection-based assays and mathematical modelling to reassess the relationship between the localization of immune cells in the liver and host protection. We found that myeloid and lymphoid resident immune cells concentrate around periportal regions. This asymmetric localization was not developmentally controlled, but resulted from sustained MYD88-dependent signalling induced by commensal bacteria in liver sinusoidal endothelial cells, which in turn regulated the composition of the pericellular matrix involved in the formation of chemokine gradients. In vivo experiments and modelling showed that this immune spatial polarization was more efficient than a uniform distribution in protecting against systemic bacterial dissemination. Together, these data reveal that liver sinusoidal endothelial cells sense the microbiome, actively orchestrating the localization of immune cells, to optimize host defence.

Covering Hierarchical Dirichlet Mixture Models on binary data to enhance genomic stratifications in onco-hematology.

Onco-hematological studies are increasingly adopting statistical mixture models to support the advancement of the genomically-driven classification systems for blood cancer. Targeting enhanced patients stratification based on the sole role of molecular biology attracted much interest and contributes to bring personalized medicine closer to reality. In onco-hematology, Hierarchical Dirichlet Mixture Models (HDMM) have become one of the preferred method to cluster the genomics data, that include the presence or absence of gene mutations and cytogenetics anomalies, into components. This work unfolds the standard workflow used in onco-hematology to improve patient stratification and proposes alternative approaches to characterize the components and to assign patient to them, as they are crucial tasks usually supported by a priori clinical knowledge. We propose (a) to compute the parameters of the multinomial components of the HDMM or (b) to estimate the parameters of the HDMM components as if they were Multivariate Fisher's Non-Central Hypergeometric (MFNCH) distributions. Then, our approach to perform patients assignments to the HDMM components is designed to essentially determine for each patient its most likely component. We show on simulated data that the patients assignment using the MFNCH-based approach can be superior, if not comparable, to using the multinomial-based approach. Lastly, we illustrate on real Acute Myeloid Leukemia data how the utilization of MFNCH-based approach emerges as a good trade-off between the rigorous multinomial-based characterization of the HDMM components and the common refinement of them based on a priori clinical knowledge.

Structural insights of a highly potent pan-neutralizing SARS-CoV-2 human monoclonal antibody.

As the coronavirus disease 2019 (COVID-19) pandemic continues, there is a strong need for highly potent monoclonal antibodies (mAbs) that are resistant against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VoCs). Here, we evaluate the potency of the previously described mAb J08 against these variants using cell-based assays and delve into the molecular details of the binding interaction using cryoelectron microscopy (cryo-EM) and X-ray crystallography. We show that mAb J08 has low nanomolar affinity against most VoCs and binds high on the receptor binding domain (RBD) ridge, away from many VoC mutations. These findings further validate the phase II/III human clinical trial underway using mAb J08 as a monoclonal therapy.

Evaluation of different computational methods for DNA methylation-based biological age.

In recent years there has been a widespread interest in researching biomarkers of aging that could predict physiological vulnerability better than chronological age. Aging, in fact, is one of the most relevant risk factors for a wide range of maladies, and molecular surrogates of this phenotype could enable better patients stratification. Among the most promising of such biomarkers is DNA methylation-based biological age. Given the potential and variety of computational implementations (epigenetic clocks), we here present a systematic review of such clocks. Furthermore, we provide a large-scale performance comparison across different tissues and diseases in terms of age prediction accuracy and age acceleration, a measure of deviance from physiology. Our analysis offers both a state-of-the-art overview of the computational techniques developed so far and a heterogeneous picture of performances, which can be helpful in orienting future research.

Vaccines and Monoclonal Antibodies as Alternative Strategies to Antibiotics to Fight Antimicrobial Resistance.

Antimicrobial resistance (AMR) is one of the most critical threats to global public health in the 21st century, causing a large number of deaths every year in both high-income and low- and middle-income countries. Vaccines and monoclonal antibodies can be exploited to prevent and treat diseases caused by AMR pathogens, thereby reducing antibiotic use and decreasing selective pressure that favors the emergence of resistant strains. Here, differences in the mechanism of action and resistance of vaccines and monoclonal antibodies compared to antibiotics are discussed. The state of the art for vaccine technologies and monoclonal antibodies are reviewed, with a particular focus on approaches validated in clinical studies. By underscoring the scope and limitations of the different emerging technologies, this review points out the complementary of vaccines and monoclonal antibodies in fighting AMR. Gaps in antigen discovery for some pathogens, as well as challenges associated with the clinical development of these therapies against AMR pathogens, are highlighted.

Clinical relevance of clonal hematopoiesis in persons aged ≥80 years.

Clonal hematopoiesis of indeterminate potential (CHIP) is associated with increased risk of cancers and inflammation-related diseases. This phenomenon becomes common in persons aged ≥80 years, in whom the implications of CHIP are not well defined. We performed a mutational screening in 1794 persons aged ≥80 years and investigated the relationships between CHIP and associated pathologies. Mutations were observed in one-third of persons aged ≥80 years and were associated with reduced survival. Mutations in JAK2 and splicing genes, multiple mutations (DNMT3A, TET2, and ASXL1 with additional genetic lesions), and variant allele frequency ≥0.096 had positive predictive value for myeloid neoplasms. Combining mutation profiles with abnormalities in red blood cell indices improved the ability of myeloid neoplasm prediction. On this basis, we defined a predictive model that identifies 3 risk groups with different probabilities of developing myeloid neoplasms. Mutations in DNMT3A, TET2, ASXL1, or JAK2 were associated with coronary heart disease and rheumatoid arthritis. Cytopenia was common in persons aged ≥80 years, with the underlying cause remaining unexplained in 30% of cases. Among individuals with unexplained cytopenia, the presence of highly specific mutation patterns was associated with myelodysplastic-like phenotype and a probability of survival comparable to that of myeloid neoplasms. Accordingly, 7.5% of subjects aged ≥80 years with cytopenia had presumptive evidence of myeloid neoplasm. In summary, specific mutational patterns define different risk of developing myeloid neoplasms vs inflammatory-associated diseases in persons aged ≥80 years. In individuals with unexplained cytopenia, mutational status may identify those subjects with presumptive evidence of myeloid neoplasms.

Estimage: a webserver hub for the computation of methylation age.

Methylage is an epigenetic marker of biological age that exploits the correlation between the methylation state of specific CG dinucleotides (CpGs) and chronological age (in years), gestational age (in weeks), cellular age (in cell cycles or as telomere length, in kilobases). Using DNA methylation data, methylage is measurable via the so called epigenetic clocks. Importantly, alterations of the correlation between methylage and age (age acceleration or deceleration) have been stably associated with pathological states and occur long before clinical signs of diseases become overt, making epigenetic clocks a potentially disruptive tool in preventive, diagnostic and also in forensic applications. Nevertheless, methylage dependency from CpGs selection, mathematical modelling, tissue specificity and age range, still makes the potential of this biomarker limited. In order to enhance model comparisons, interchange, availability, robustness and standardization, we organized a selected set of clocks within a hub webservice, EstimAge (Estimate of methylation Age, http://estimage.iac.rm.cnr.it), which intuitively and informatively enables quick identification, computation and comparison of available clocks, with the support of standard statistics.

Canine smooth muscle tumors: A clinicopathological study.

Canine smooth muscle tumors (SMTs) commonly develop in the alimentary and female genital tracts and less frequently in soft tissue. The definition of histological criteria of malignancy is less detailed for SMTs in dogs than in humans. This study evaluated the clinicopathologic features of canine SMTs and compared the veterinary and human medical criteria of malignancy. A total of 105 canine SMTs were evaluated histologically and classified according to both veterinary and human criteria. The Ki67 labeling index was assessed in all SMTs. Estrogen receptor (ER) and progesterone receptor (PR) expression was evaluated for soft tissue SMTs. Follow-up data were available in 25 cases. SMTs were diagnosed in the female genital tract (42%), alimentary tract (22%), and soft tissue (20%). Soft tissue SMTs frequently arose in the perigenital area, pelvic cavity, and retroperitoneum. A subset of soft tissue SMTs expressed ER and/or PR, resembling the gynecologic type of soft tissue SMT in humans. SMTs were less frequently malignant when assessed with human criteria than with veterinary criteria, better reflecting their benign behavior, especially in the genital tract where human criteria tolerate a higher mitotic count for leiomyoma. Decreased differentiation was correlated with increased proliferation, necrosis, and reduced desmin expression. Mitotic count, Ki67 labeling index, and necrosis were correlated with metastases and tumor-related death. Further prognostic studies are warranted to confirm the better performance of the human criteria when assessing SMT malignancy, especially genital cases, to confirm their usefulness in ER/PR-expressing soft tissue SMTs, and to better define the most useful prognostic parameters for canine SMTs.

Impact of concurrency on the performance of a whole exome sequencing pipeline.

BACKGROUND: Current high-throughput technologies-i.e. whole genome sequencing, RNA-Seq, ChIP-Seq, etc.-generate huge amounts of data and their usage gets more widespread with each passing year. Complex analysis pipelines involving several computationally-intensive steps have to be applied on an increasing number of samples. Workflow management systems allow parallelization and a more efficient usage of computational power. Nevertheless, this mostly happens by assigning the available cores to a single or few samples' pipeline at a time. We refer to this approach as naive parallel strategy (NPS). Here, we discuss an alternative approach, which we refer to as concurrent execution strategy (CES), which equally distributes the available processors across every sample's pipeline. RESULTS: Theoretically, we show that the CES results, under loose conditions, in a substantial speedup, with an ideal gain range spanning from 1 to the number of samples. Also, we observe that the CES yields even faster executions since parallelly computable tasks scale sub-linearly. Practically, we tested both strategies on a whole exome sequencing pipeline applied to three publicly available matched tumour-normal sample pairs of gastrointestinal stromal tumour. The CES achieved speedups in latency up to 2-2.4 compared to the NPS. CONCLUSIONS: Our results hint that if resources distribution is further tailored to fit specific situations, an even greater gain in performance of multiple samples pipelines execution could be achieved. For this to be feasible, a benchmarking of the tools included in the pipeline would be necessary. It is our opinion these benchmarks should be consistently performed by the tools' developers. Finally, these results suggest that concurrent strategies might also lead to energy and cost savings by making feasible the usage of low power machine clusters.

Insights From Liver-Humanized Mice on Cholesterol Lipoprotein Metabolism and LXR-Agonist Pharmacodynamics in Humans.

BACKGROUND AND AIMS: Genetically modified mice have been used extensively to study human disease. However, the data gained are not always translatable to humans because of major species differences. Liver-humanized mice (LHM) are considered a promising model to study human hepatic and systemic metabolism. Therefore, we aimed to further explore their lipoprotein metabolism and to characterize key hepatic species-related, physiological differences. APPROACH AND RESULTS: Fah-/- , Rag2-/- , and Il2rg-/- knockout mice on the nonobese diabetic (FRGN) background were repopulated with primary human hepatocytes from different donors. Cholesterol lipoprotein profiles of LHM showed a human-like pattern, characterized by a high ratio of low-density lipoprotein to high-density lipoprotein, and dependency on the human donor. This pattern was determined by a higher level of apolipoprotein B100 in circulation, as a result of lower hepatic mRNA editing and low-density lipoprotein receptor expression, and higher levels of circulating proprotein convertase subtilisin/kexin type 9. As a consequence, LHM lipoproteins bind to human aortic proteoglycans in a pattern similar to human lipoproteins. Unexpectedly, cholesteryl ester transfer protein was not required to determine the human-like cholesterol lipoprotein profile. Moreover, LHM treated with GW3965 mimicked the negative lipid outcomes of the first human trial of liver X receptor stimulation (i.e., a dramatic increase of cholesterol and triglycerides in circulation). Innovatively, LHM allowed the characterization of these effects at a molecular level. CONCLUSIONS: LHM represent an interesting translatable model of human hepatic and lipoprotein metabolism. Because several metabolic parameters displayed donor dependency, LHM may also be used in studies for personalized medicine.

Polarly Localized EccE1 Is Required for ESX-1 Function and Stabilization of ESX-1 Membrane Proteins in Mycobacterium tuberculosis.

Mycobacterium tuberculosis is a slow-growing intracellular bacterium with the ability to induce host cell death and persist indefinitely in the human body. This pathogen uses the specialized ESX-1 secretion system to secrete virulence factors and potent immunogenic effectors required for disease progression. ESX-1 is a multisubunit apparatus with a membrane complex that is predicted to form a channel in the cytoplasmic membrane. In M. tuberculosis this complex is composed of five membrane proteins: EccB1, EccCa1, EccCb1, EccD1, and EccE1 In this study, we have characterized the membrane component EccE1 and found that deletion of eccE1 lowers the levels of EccB1, EccCa1, and EccD1, thereby abolishing ESX-1 secretion and attenuating M. tuberculosisex vivo Surprisingly, secretion of EspB was not affected by loss of EccE1 Furthermore, EccE1 was found to be a membrane- and cell wall-associated protein that needs the presence of other ESX-1 components to assemble into a stable complex at the poles of M. tuberculosis Overall, this investigation provides new insights into the role of EccE1 and its localization in M. tuberculosisIMPORTANCE Tuberculosis (TB), the world's leading cause of death of humans from an infectious disease, is caused by the intracellular bacterium Mycobacterium tuberculosis The development of successful strategies to control TB requires better understanding of the complex interactions between the pathogen and the human host. We investigated the contribution of EccE1, a membrane protein, to the function of the ESX-1 secretion system, the major virulence determinant of M. tuberculosis By combining genetic analysis of selected mutants with eukaryotic cell biology and proteomics, we demonstrate that EccE1 is critical for ESX-1 function, secretion of effector proteins, and pathogenesis. Our research improves knowledge of the molecular basis of M. tuberculosis virulence and enhances our understanding of pathogenesis.

Methylation data imputation performances under different representations and missingness patterns.

BACKGROUND: High-throughput technologies enable the cost-effective collection and analysis of DNA methylation data throughout the human genome. This naturally entails missing values management that can complicate the analysis of the data. Several general and specific imputation methods are suitable for DNA methylation data. However, there are no detailed studies of their performances under different missing data mechanisms -(completely) at random or not- and different representations of DNA methylation levels (ß and M-value). RESULTS: We make an extensive analysis of the imputation performances of seven imputation methods on simulated missing completely at random (MCAR), missing at random (MAR) and missing not at random (MNAR) methylation data. We further consider imputation performances on the popular ß- and M-value representations of methylation levels. Overall, ß-values enable better imputation performances than M-values. Imputation accuracy is lower for mid-range ß-values, while it is generally more accurate for values at the extremes of the ß-value range. The MAR values distribution is on the average more dense in the mid-range in comparison to the expected ß-value distribution. As a consequence, MAR values are on average harder to impute. CONCLUSIONS: The results of the analysis provide guidelines for the most suitable imputation approaches for DNA methylation data under different representations of DNA methylation levels and different missing data mechanisms.

Missing value estimation methods for DNA methylation data.

MOTIVATION: DNA methylation is a stable epigenetic mark with major implications in both physiological (development, aging) and pathological conditions (cancers and numerous diseases). Recent research involving methylation focuses on the development of molecular age estimation methods based on DNA methylation levels (mAge). An increasing number of studies indicate that divergences between mAge and chronological age may be associated to age-related diseases. Current advances in high-throughput technologies have allowed the characterization of DNA methylation levels throughout the human genome. However, experimental methylation profiles often contain multiple missing values that can affect the analysis of the data and also mAge estimation. Although several imputation methods exist, a major deficiency lies in the inability to cope with large datasets, such as DNA methylation chips. Specific methods for imputing missing methylation data are therefore needed. RESULTS: We present a simple and computationally efficient imputation method, metyhLImp, based on linear regression. The rationale of the approach lies in the observation that methylation levels show a high degree of inter-sample correlation. We performed a comparative study of our approach with other imputation methods on DNA methylation data of healthy and disease samples from different tissues. Performances have been assessed both in terms of imputation accuracy and in terms of the impact imputed values have on mAge estimation. In comparison to existing methods, our linear regression model proves to perform equally or better and with good computational efficiency. The results of our analysis provide recommendations for accurate estimation of missing methylation values. AVAILABILITY AND IMPLEMENTATION: The R-package methyLImp is freely available at https://github.com/pdilena/methyLImp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

EspL is essential for virulence and stabilizes EspE, EspF and EspH levels in Mycobacterium tuberculosis.

The ESX-1, type VII, secretion system represents the major virulence determinant of Mycobacterium tuberculosis, one of the most successful intracellular pathogens. Here, by combining genetic and high-throughput approaches, we show that EspL, a protein of 115 amino acids, is essential for mediating ESX-1-dependent virulence and for stabilization of EspE, EspF and EspH protein levels. Indeed, an espL knock-out mutant was unable to replicate intracellularly, secrete ESX-1 substrates or stimulate innate cytokine production. Moreover, proteomic studies detected greatly reduced amounts of EspE, EspF and EspH in the espL mutant as compared to the wild type strain, suggesting a role for EspL as a chaperone. The latter conclusion was further supported by discovering that EspL interacts with EspD, which was previously demonstrated to stabilize the ESX-1 substrates and effector proteins, EspA and EspC. Loss of EspL also leads to downregulation in M. tuberculosis of WhiB6, a redox-sensitive transcriptional activator of ESX-1 genes. Overall, our data highlight the importance of a so-far overlooked, though conserved, component of the ESX-1 secretion system and begin to delineate the role played by EspE, EspF and EspH in virulence and host-pathogen interaction.

Transcription facilitated genome-wide recruitment of topoisomerase I and DNA gyrase.

Movement of the transcription machinery along a template alters DNA topology resulting in the accumulation of supercoils in DNA. The positive supercoils generated ahead of transcribing RNA polymerase (RNAP) and the negative supercoils accumulating behind impose severe topological constraints impeding transcription process. Previous studies have implied the role of topoisomerases in the removal of torsional stress and the maintenance of template topology but the in vivo interaction of functionally distinct topoisomerases with heterogeneous chromosomal territories is not deciphered. Moreover, how the transcription-induced supercoils influence the genome-wide recruitment of DNA topoisomerases remains to be explored in bacteria. Using ChIP-Seq, we show the genome-wide occupancy profile of both topoisomerase I and DNA gyrase in conjunction with RNAP in Mycobacterium tuberculosis taking advantage of minimal topoisomerase representation in the organism. The study unveils the first in vivo genome-wide interaction of both the topoisomerases with the genomic regions and establishes that transcription-induced supercoils govern their recruitment at genomic sites. Distribution profiles revealed co-localization of RNAP and the two topoisomerases on the active transcriptional units (TUs). At a given locus, topoisomerase I and DNA gyrase were localized behind and ahead of RNAP, respectively, correlating with the twin-supercoiled domains generated. The recruitment of topoisomerases was higher at the genomic loci with higher transcriptional activity and/or at regions under high torsional stress compared to silent genomic loci. Importantly, the occupancy of DNA gyrase, sole type II topoisomerase in Mtb, near the Ter domain of the Mtb chromosome validates its function as a decatenase.

EspC forms a filamentous structure in the cell envelope of Mycobacterium tuberculosis and impacts ESX-1 secretion.

Pathogenicity of Mycobacterium tuberculosis (M. tb) is mediated by the ESX-1 secretion system, which exports EsxA and EsxB, the major virulence factors that are co-secreted with EspA and EspC. Functional information about ESX-1 components is scarce. Here, it was shown that EspC associates with EspA in the cytoplasm and membrane, then polymerizes during secretion from M. tb. EspC was localized by immuno-gold electron microscopy in whole cells or cryosections as a surface-exposed filamentous structure that seems to span the cell envelope. Consistent with these findings, purified EspC homodimerizes via disulphide bond formation, multimerizes and self-assembles into long filaments in vitro. The C-terminal domain is required for multimerization as truncation and selected point mutations therein impact EspC filament formation, thus reducing secretion of EsxA and causing attenuation of M. tb. The data are consistent with EspC serving either as a modulator of ESX-1 function or as a component of the secretion apparatus.