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Ageing and MPTP- sensitivity depend on molecular and ultrastructural signatures of astroglia and microglia in mice nigra

Both astroglia and microglia show region-specific distribution in CNS and often maladapt to age-associated alterations within their niche. Studies on autopsied substantia nigra (SN) of Parkinsons disease (PD) patients and experimental models propose gliosis as a trigger for neuronal loss. Epidemiological studies propose an ethnic bias in PD prevalence, since Caucasians are more susceptible than non-whites. Similarly, different mice strains are variably sensitive to MPTP. We had earlier likened divergent MPTP-sensitivity of C57BL/6J and CD-1 mice with differential susceptibility to PD, based on the numbers of SN neurons. Here, we examined whether the variability was incumbent to inter-strain differences in glial features of male C57BL/6J and CD-1 mice. Stereological counts showed relatively more microglia and fewer astrocytes in the SN of normal C57BL/6J mice, suggesting persistence of an immune-vigilant state. MPTP-induced microgliosis and astrogliosis in both strains, suggests their involvement in pathogenesis. ELISA of pro-inflammatory cytokines in the ventral-midbrain revealed augmentation of TNF- and IL-6 at middle-age in both strains that reduced at old-age, suggesting middle-age as a critical, inflamm-aging associated time-point. TNF- levels were high in C57BL/6J, through aging and post-MPTP; while IL-6 and IL-1{beta} were upregulated at old-age. CD-1 had higher levels of anti-inflammatory cytokine TGF-{beta}. MPTP-challenge caused upregulation of enzymes MAO-A, MAO-B and iNOS in both strains. Post-MPTP enhancement in fractalkine and hemeoxygenase-1; may be neuron-associated compensatory signals. Ultrastructural observations of elongated astroglial/microglial mitochondria vis-a-vis the shrunken ones in neurons, suggest a scale-up of their functions with neurotoxic consequences. Thus, astroglia and microglia modulate aging and PD-susceptibility. HighlightsO_LISubstantia nigra of C57BL/6J and CD-1 show no baseline differences in glial numbers C_LIO_LIBoth mice show age and MPTP-induced gliosis in the substantia nigra pars compacta C_LIO_LICD-1 nigra has lower levels of pro- and higher levels of anti-inflammatory cytokines C_LIO_LITilt of balance between pro- and anti-inflammatory cytokines begins at middle age C_LIO_LIAstrocytes and microglia show elongated mitochondria and intact ER upon MPTP-injection C_LI

neuroscience↗

The Ensembl COVID-19 resource: Ongoing integration of public SARS-CoV-2 data

The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser, incorporating a new Ensembl gene set, multiple variant sets (including novel variation calls), and annotation from several relevant resources integrated into the reference SARS-CoV-2 assembly. This work included key adaptations of existing Ensembl genome annotation methods to model ribosomal slippage, stringent filters to elucidate the highest confidence variants and utilisation of our comparative genomics pipelines on viruses for the first time. Since May 2020, the content has been regularly updated and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.

bioinformatics↗

A comprehensive transcriptome analysis reveals broader but weaker host response of SARS-CoV-2 than SARS-CoV

COVID-19, which has resulted a worldwide health crisis with more than 74.9 million confirmed cases worldwide by December 2020, is caused by a newly emerging coronavirus identified and named SARS-CoV-2 in February in Wuhan, China. Experiences in defeating SARS, which infested during 2002-2003, can be used in treating the new disease. However, comparative genomics and epidemiology studies have shown much difference between SARS-CoV and SARS-CoV-2, which underlies the different clinical features and therapies in between those two diseases. Further studies comparing transcriptomes infected by these two viruses to uncover the differences in host responses would be necessary. Here we conducted a comprehensive transcriptome analysis of SARS-CoV and SARS-CoV-2-infected human cell lines, including Caco-2, Calu-3, H1299. Clustering analysis and expression of ACE2 show that SARS-CoV-2 has broader but weaker infection, where the largest discrepancy occurs in the epithelial lung cancer cell, Calu-3. SARS-CoV-2 genes also show less tissue specificity than SARS-CoV genes. Furthermore, we detected more general but moderate immune responses in SARS-CoV-2 infected transcriptomes by comparing weighted gene co-expression networks and modules. Our results suggest a different immune therapy and treatment scheme for COVID-19 patients than the ones used on SARS patients. The wider but weaker permissiveness and host responses of virus infection may also imply a long-term existence of SARS-CoV-2 among human populations.

microbiology↗

From infection to immunity: understanding the response to SARS-CoV2 through in-silico modeling

BackgroundImmune system conditions of the patient is a key factor in COVID-19 infection survival. A growing number of studies have focused on immunological determinants to develop better biomarkers for therapies. AimThe dynamics of the insurgence of immunity is at the core of the both SARS-CoV-2 vaccine development and therapies. This paper addresses a fundamental question in the management of the infection: can we describe the insurgence (and the span) of immunity in COVID-19? The in-silico model developed here answers this question at individual (personalized) and population levels. We simulate the immune response to SARS-CoV-2 and analyze the impact of infecting viral load, affinity to the ACE2 receptor and age in the artificially infected population on the course of the disease. MethodsWe use a stochastic agent-based immune simulation platform to construct a virtual cohort of infected individuals with age-dependent varying degree of immune competence. We use a parameter setting to reproduce known inter-patient variability and general epidemiological statistics. ResultsWe reproduce in-silico a number of clinical observations and we identify critical factors in the statistical evolution of the infection. In particular we evidence the importance of the humoral response over the cytotoxic response and find that the antibody titers measured after day 25 from the infection is a prognostic factor for determining the clinical outcome of the infection. Our modeling framework uses COVID-19 infection to demonstrate the actionable effectiveness of simulating the immune response at individual and population levels. The model developed is able to explain and interpret observed patterns of infection and makes verifiable temporal predictions. Within the limitations imposed by the simulated environment, this work proposes in a quantitative way that the great variability observed in the patient outcomes in real life can be the mere result of subtle variability in the infecting viral load and immune competence in the population. In this work we i) show the power of model predictions, ii) identify the clinical end points that could be more suitable for computational modeling of COVID-19 immune response, iii) define the resolution and amount of data required to empower this class of models for translational medicine purposes and, iv) we exemplify how computational modeling of immune response provides an important view to discuss hypothesis and design new experiments, in particular paving the way to further investigations about the duration of vaccine-elicited immunity especially in the view of the blundering effect of immunesenescence.

bioinformatics↗

Frequency-dependent competition between strains imparts resilience to perturbations in a model of Plasmodium falciparum malaria transmission.

In high-transmission endemic regions, local populations of Plasmodium falciparum exhibit vast diversity of the var genes encoding its major surface antigen, with each parasite comprising multiple copies from this diverse gene pool. This strategy to evade the immune system through large combinatorial antigenic diversity is common to other hyperdiverse pathogens. It underlies a series of fundamental epidemiological characteristics, including large reservoirs of transmission from high prevalence of asymptomatics and long-lasting infections. Previous theory has shown that negative frequency-dependent selection (NFDS) mediated by the acquisition of specific immunity by hosts structures the diversity of var gene repertoires (strains), in a pattern of limiting similarity that is both non-random and non-neutral. A combination of stochastic agent-based models and network analyses has enabled the development and testing of theory in these complex adaptive systems, where assembly of local parasite diversity occurs under frequency-dependent selection and large pools of variation. We show here the application of these approaches to theory comparing the resilience of the malaria transmission system to intervention when strain diversity is assembled under (competition-based) selection vs. a form of neutrality, where immunity depends only on the number but not the genetic identity of previous infections. The transmission system is considerably more resilient under NFDS, exhibiting a lower extinction probability despite comparable prevalence during intervention. We explain this pattern on the basis of the structure of strain diversity, in particular the more pronounced fraction of highly dissimilar parasites. For simulations that survive intervention, prevalence under specific immunity is lower than under neutrality, because the recovery of diversity is considerably slower than that of prevalence and decreased var gene diversity reduces parasite transmission. A Principal Component Analysis of network features describing parasite similarity reveals that despite lower overall diversity, NFDS is quickly restored after intervention constraining strain structure and maintaining patterns of limiting similarity important to parasite persistence. Given the resulting resilience to perturbations, intervention efforts will likely require longer times than the usual practice to eliminate P. falciparum populations. We discuss implications of our findings and potential analogies for ecological communities with non-neutral assembly processes involving frequency-dependence.

ecology↗

Patterns of within-host genetic diversity in SARS-CoV-2

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1,181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within and between host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

genomics↗

Retroviral Infection of Human Neurospheres and Use of Stem Cell EVs to Repair Cellular Damage

HIV-1 remains an incurable infection that is associated with substantial economic and epidemiologic impacts. HIV-associated neurocognitive disorders (HAND) are commonly linked with HIV-1 infection; despite the development of combination antiretroviral therapy (cART), HAND is still reported to affect at least 50% of HIV-1 infected individuals. It is believed that the over-amplification of inflammatory pathways, along with release of toxic viral proteins from infected cells, are primarily responsible for the neurological damage that is observed in HAND; however, the underlying mechanisms are not well-defined. Therefore, there is an unmet need to develop more physiologically relevant and reliable platforms for studying these pathologies. In recent years, neurospheres derived from induced pluripotent stem cells (iPSCs) have been utilized to model the effects of different neurotropic viruses. Here, we report the generation of neurospheres from iPSC-derived neural progenitor cells (NPCs) and we show that these cultures are permissive to retroviral (e.g. HIV-1, HTLV-1) replication. In addition, we also examine the potential effects of stem cell derived extracellular vesicles (EVs) on HIV-1 damaged cells as there is abundant literature supporting the reparative and regenerative properties of stem cell EVs in the context of various CNS pathologies. Consistent with the literature, our data suggests that stem cell EVs may modulate neuroprotective and anti-inflammatory properties in damaged cells. Collectively, this study demonstrates the feasibility of NPC-derived neurospheres for modeling HIV-1 infection and, subsequently, highlights the potential of stem cell EVs for rescuing cellular damage induced by HIV-1 infection.

cell biology↗

Genomic insights of high-risk clones of ESBL-producing Escherichia coli isolated from community infections and commercial meat in Southern Brazil

During a microbiological and genomic surveillance study to investigate the molecular epidemiology of extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli from community-acquired urinary tract infections (UTI) and commercial meat samples, in a Brazilian city with a high occurrence of infections by ESBL-producing bacteria, we have identified the presence of CTX-M (-55, -27, -24, -15, -14 and -2)-producing E. coli belonging to the international clones ST354, ST131, ST117, and ST38. The ST131 was more prevalent in human samples, and worryingly the high-risk ST131-C1-M27 was identified in human infections for the first time. We also detected CTX-M-55-producing E. coli ST117 isolates from meat samples (i.e., chicken and pork) and human infections. Moreover, we have identified the important clone CTX-M-24-positive E. coli ST354 from human samples in Brazil for the first time. In brief, our results suggest a potential of commercialized meat as a reservoir of high-priority E. coli lineages in the community. In contrast, the identification of E. coli ST131-C1-M27 indicates that novel pandemic clones have emerged in Brazil, constituting a public health issue.

microbiology↗

Structure-function investigation of a new VUI-202012/01 SARS-CoV-2 variant

The SARS-CoV-2 (Severe Acute Respiratory Syndrome-Coronavirus) has accumulated multiple mutations during its global circulation. Recently, a new strain of SARS-CoV-2 (VUI 202012/01) had been identified leading to sudden spike in COVID-19 cases in South-East England. The strain has accumulated 23 mutations which have been linked to its immune evasion and higher transmission capabilities. Here, we have highlighted structural-function impact of crucial mutations occurring in spike (S), ORF8 and nucleocapsid (N) protein of SARS-CoV-2. Some of these mutations might confer higher fitness to SARS-CoV-2. SummarySince initial outbreak of COVID-19 in Wuhan city of central China, its causative agent; SARS-CoV-2 virus has claimed more than 1.7 million lives out of 77 million populations and still counting. As a result of global research efforts involving public-private-partnerships, more than 0.2 million complete genome sequences have been made available through Global Initiative on Sharing All Influenza Data (GISAID). Similar to previously characterized coronaviruses (CoVs), the positive-sense single-stranded RNA SARS-CoV-2 genome codes for ORF1ab non-structural proteins (nsp(s)) followed by ten or more structural/nsps [1, 2]. The structural proteins include crucial spike (S), nucleocapsid (N), membrane (M), and envelope (E) proteins. The S protein mediates initial contacts with human hosts while the E and M proteins function in viral assembly and budding. In recent reports on evolution of SARS-CoV-2, three lineage defining non-synonymous mutations; namely D614G in S protein (Clade G), G251V in ORF3a (Clade V) and L84S in ORF 8 (Clade S) were observed [2-4]. The latest pioneering works by Plante et al and Hou et al have shown that compared to ancestral strain, the ubiquitous D614G variant (clade G) of SARS-CoV-2 exhibits efficient replication in upper respiratory tract epithelial cells and transmission, thereby conferring higher fitness [5, 6]. As per latest WHO reports on COVID-19, a new strain referred as SARS-CoV-2 VUI 202012/01 (Variant Under Investigation, year 2020, month 12, variant 01) had been identified as a part of virological and epidemiological analysis, due to sudden rise in COVID-19 detected cases in South-East England [7]. Preliminary reports from UK suggested higher transmissibility (increase by 40-70%) of this strain, escalating Ro (basic reproduction number) of virus to 1.5-1.7 [7, 8]. This apparent fast spreading variant inculcates 23 mutations; 13 non-synonymous, 6 synonymous and 4 amino acid deletions [7]. In the current scenario, where immunization programs have already commenced in nations highly affected by COVID-19, advent of this new strain variant has raised concerns worldwide on its possible role in disease severity and antibody responses. The mutations also could also have significant impact on diagnostic assays owing to S gene target failures.

bioinformatics↗

Distinct mutations and lineages of SARS-CoV-2 virus in the early phase of COVID-19 global pandemic and subsequent global expansion

A novel coronavirus, SARS-CoV-2, has caused over 190 million cases and over 4 million deaths worldwide since it occurred in December 2019 in Wuhan, China. Here we conceptualized the temporospatial evolutionary and expansion dynamics of SARS-CoV-2 by taking a series of cross-sectional view of viral genomes from early outbreak in January 2020 in Wuhan to early phase of global ignition in early April, and finally to the subsequent global expansion by late December 2020. Based on the phylogenetic analysis of the early patients in Wuhan, Wuhan/WH04/2020 is supposed to be a more appropriate reference genome of SARS-CoV-2, instead of the first sequenced genome Wuhan-Hu-1. By scrutinizing the cases from the very early outbreak, we found a viral genotype from the Seafood Market in Wuhan featured with two concurrent mutations (i.e. M type) had become the overwhelmingly dominant genotype (95.3%) of the pandemic one year later. By analyzing 4,013 SARS-CoV-2 genomes from different continents by early April, we were able to interrogate the viral genomic composition dynamics of initial phase of global ignition over a timespan of 14-week. 11 major viral genotypes with unique geographic distributions were also identified. WE1 type, a descendant of M and predominantly witnessed in western Europe, consisted a half of all the cases (50.2%) at the time. The mutations of major genotypes at the same hierarchical level were mutually exclusive, which implying that various genotypes bearing the specific mutations were propagated during human-to-human transmission, not by accumulating hot-spot mutations during the replication of individual viral genomes. As the pandemic was unfolding, we also used the same approach to analyze 261,323 SARS-CoV-2 genomes from the world since the outbreak in Wuhan (i.e. including all the publicly available viral genomes) in order to recapitulate our findings over one-year timespan. By 25 December 2020, 95.3% of global cases were M type and 93.0% of M-type cases were WE1. In fact, at present all the four variants of concern (VOC) are the descendants of WE1 type. This study demonstrates the viral genotypes can be utilized as molecular barcodes in combination with epidemiologic data to monitor the spreading routes of the pandemic and evaluate the effectiveness of control measures. Moreover, the dynamics of viral mutational spectrum in the study may help the early identification of new strains in patients to reduce further spread of infection, guide the development of molecular diagnosis and vaccines against COVID-19, and help assess their accuracy and efficacy in real world at real time.

genomics↗

West Nile virus detection in horses in three Brazilian states.

We report genetic evidence of WNV circulation from southern and northeastern Brazilian states isolated from equine red blood cells. In the northeastern state the tenth human case was also detected, presenting neuroinvasive disease compatible with WNV infection. Our analyses demonstrate that much is still unknown on the virus local epidemiology. We advocate for a shift to active surveillance, to ensure adequate control for future epidemics with spill-over potential to humans.

genomics↗

A Multi-dimensional Integrative Scoring Framework for Predicting Functional Regions in the Human Genome

Attempts to identify and prioritize functional DNA elements in coding and noncoding regions, particularly through use of in silico functional annotation data,continue to increase in popularity. However, specific functional roles may vary widely from one variant to another, making it challenging to summarize different aspects of variant function. Here we propose Multi-dimensional Annotation Class Integrative Estimation (MACIE), an unsupervised multivariate mixed model framework capable of integrating annotations of diverse origin to assess multi-dimensional functional roles for both coding and noncoding variants. Unlike existing one-dimensional scoring methods, MACIE views variant functionality as a composite attribute encompassing multiple characteristics, and estimates the joint posterior functional probability vector of each genomic position, a quantity that offers richer and more interpretable information in the presence of multiple aspects of functionality. Applied to a variety of independent coding and non-coding datasets, MACIE demonstrates powerful and robust performance in discriminating between functional and non-functional variants. We also show an application of MACIE to fine-mapping using lipids GWAS summary statistics data from the European Network for Genetic and Genomic Epidemiology Consortium.

genetics↗

Incidence and Characteristics of Co-infection and Secondary Infection in Patients with COVID-19

ObjectiveThe etiology and epidemiology of co-infection and secondary infection in COVID-19 patients remain unknown. The study aims to investigate the occurrence and characteristics of co-infection and secondary infection in COVID-19 patients, mainly focusing on Streptococcus pneumoniae co-infections. MethodsThis study was a prospective, observational cohort study of the inpatients diagnosed with COVID-19 in two designated hospitals in south China enrolled between Jan 11 and Feb 22, 2020. The urine specimen was collected on admission and applied for pneumococcal urinary antigen tests (PUATs). Demographic, clinical and microbiological data of patients were recorded simultaneously. ResultA total of 146 patients with a confirm diagnosis of COVID-19 at the median age of 50.0 years (IQR 36.0-61.0) were enrolled, in which, 16 (11.0%) were classified as severe cases and 130 (89.0%) as non-severe cases. Of the enrolled patients, only 3 (2.1%) were considered to present the co-infection, in which 1 was co-infected with S.pneumoniae, 1 with B. Ovatus infection and the other one with Influenza A virus infection. Secondary infection occurred in 16 patients, with S. maltophilia as the most commonly isolated pathogen (43.8%), followed by P. aeruginosa (25.0%), E. aerogenes (25.0%), C. parapsilosis (25.0%) and A. fumigates (18.8%). ConclusionPatients with confirmed COVID-19 were rarely co-infected with Streptococcus pneumoniae or other pathogens, indicating that the application of antibiotics against CAP on admission may not be necessary in the treatment of COVID-19 cases.

microbiology↗

Surveillance of Shiga toxin-producing Escherichia coli associated bloody diarrhea in Argentina

In Argentina, the hemolytic uremic syndrome associated with Shiga toxin-producing Escherichia coli (STEC-HUS) infection is endemic, and reliable data about prevalence and risk factors are available since 2000. However, information about STEC-associated bloody diarrhea (BD) cases is limited. A prospective study was carried out in seven tertiary-hospitals and 18 Referral Units from different regions, aiming to determine (i) STEC-positive BD cases frequency in 714 children aged 1 to 9 years old; and (ii) rate of progression to HUS. The number and regional distribution of STEC-HUS cases assisted in the same hospitals and period was also assessed. A total of 29 (4.1%) STEC-positive BD cases were confirmed by Shiga Toxin Quik Chek (STQC) and/or mPCR. The highest frequencies were found in the Southern region (Neuquen, 8.7%; Bahia Blanca, 7.9%), in children between 12 and 23 month of age (8.8%), during summertime. Four (13.8%) cases progressed to HUS, three to five days after BD onset. Twenty-seven STEC-HUS children mainly under 5 years old (77.8%) were enrolled, 51.9% were female; 44% were Stx-positive by STQC and all by mPCR. The most common serotypes were O157:H7 and O145:H28 and prevalent genotypes were stx2a-only or associated, both among BD and HUS cases. Considering the endemic behavior of HUS and its impact on public health, it is important to have updated information about the epidemiology of the diarrheal disease for early recognition of infected patients and initiation of supportive treatment. Finally, it also gives the opportunity to respond to outbreak situations effectively and in timely manner.

microbiology↗

Distinguishing gene flow between malaria parasite populations

Measuring gene flow between malaria parasite populations in different geographic locations can provide strategic information for malaria control interventions. Multiple important questions pertaining to the design of such studies remain unanswered, limiting efforts to operationalize genomic surveillance tools for routine public health use. This report evaluates numerically the ability to distinguish different levels of gene flow between malaria populations, using different amounts of real and simulated data, where data are simulated using parameters that approximate different epidemiological conditions. Specifically, using Plasmodium falciparum whole genome sequence data and sequence data simulated for a metapopulation with different migration rates and effective population sizes, we compare two estimators of gene flow, explore the number of genetic markers and number of individuals required to reliably rank highly connected locations, and describe how these thresholds change given different effective population sizes and migration rates. Our results have implications for the design and implementation of malaria genomic surveillance efforts.

genomics↗

Chikungunya virus ECSA lineage reintroduction in the northeasternmost region of Brazil

The Northeast region of Brazil registered the second highest incidence proportion of chikungunya fever in 2019. In that year an outbreak consisting of patients presented with febrile disease associated with joint pain were reported by the public primary health care service in the city of Natal, Rio Grande do Norte state, in March 2019. At first, the aetiological agent of the disease was undetermined. Since much is still unknown about chikungunya virus (CHIKV) genomic diversity and evolutionary history in this northeasternmost state, we used a combination of portable whole genome sequencing, molecular clock, and epidemiological analyses that revealed the re-introduction of the CHIKV East-Central-South-African (ECSA) lineage into Rio Grande do Norte. We estimated CHIKV ECSA lineage was first introduced into Rio Grande do Norte in early June 2014, while the 2019 outbreak clade diverged around April 2018 during a period of increased chikungunya incidence in the Southeast region, which might have acted as a source of virus dispersion towards the Northeast region. Together, these results confirm the ECSA lineage continues to spread across the country through interregional importation events likely mediated by human mobility. HIGHLIGHTSCHIKV ECSA lineage introduction into Rio Grande do Norte state, Northeast Brazil, was estimated to early June 2014 At least two CHIKV importation events occurred in Rio Grande do Norte state, Brazil The 2019 chikungunya outbreak in Rio Grande do Norte was likely caused by a second event of CHIKV introduction imported from Rio de Janeiro state.

genomics↗

Rigid monoclonal antibodies improve detection of SARS-CoV-2 nucleocapsid protein

Monoclonal antibodies (mAbs) are the basis of treatments and diagnostics for pathogens and other biological phenomena. We conducted a structural characterization of mAbs against the N-terminal domain of nucleocapsid protein (NPNTD) from SARS-CoV-2 using small angle X-ray scattering (SAXS). Our solution-based results distinguished the mAbs flexibility and how this flexibility impacts the assembly of multiple mAbs on an antigen. By pairing two mAbs that bind different epitopes on the NPNTD, we show that flexible mAbs form a closed sandwich-like complex. With rigid mAbs, a juxtaposition of the Fabs is prevented, enforcing a linear arrangement of the mAb pair, which facilitates further mAb polymerization. In a modified sandwich ELISA, we show the rigid mAb-pairings with linear polymerization led to increased NPNTD detection sensitivity. These enhancements can expedite the development of more sensitive and selective antigen-detecting point-of-care lateral flow devices (LFA), key for early diagnosis and epidemiological studies of SARS-CoV-2 and other pathogens.

biophysics↗

Towards a mathematical understanding of colonization resistance

Microbial community composition and dynamics are key to health and disease. Explaining the forces generating and shaping diversity in the microbial consortia making up our bodys defenses is a major aim of current research in microbiology. For this, tractable models are needed, that bridge the gap between observations of patterns and underlying mechanisms. While most microbial dynamics models are based on the Lotka-Volterra framework, we still do not have an analytic quantity for colonization resistance, by which a microbial systems fitness as a whole can be understood. Here, inspired by an epidemiological perspective, we propose a rather general modeling framework whereby colonization resistance can be clearly mathematically defined and studied. In our model, N similar species interact with each other through a co-colonization interaction network encompassing pairwise competition and cooperation, abstractly mirroring how organisms effectively modify their micro-scale environment in relation to others. This formulation relies on a generic notion of shared resources between members of a consortium, yielding explicit frequency-dependent dynamics among N species, in the form of a replicator equation, and offering a precise definition of colonization resistance. We demonstrate that colonization resistance arises and evolves naturally in a multispecies system as a collective quadratic term in a replicator equation, describing dynamic mean invasion fitness. Each pairwise invasion growth rate between two ecological partners, [Formula], is derived explicitly from species asymmetries and mean traits. This makes the systemic colonization resistance [Formula] also an emergent function of global mean-field parameters and trait variation architecture, weighted by the evolving relative abundances among species. In particular, if the underlying invasion fitness matrix {Lambda} displays species-specific invasiveness or invasibility structure, colonization resistance will be insensitive to mean micro-scale cooperation or competition. However, in general, colonization resistance depends on and may undergo critical transitions with changes in mean environment, e.g. cooperation and growth level in a community. We illustrate several key links between our proposed measure of colonization resistance and invader success, including sensitivity to timing, and to the intrinsic pairwise invasion architecture of the resident community. Our simulations reveal that symmetric and invader-driven mutual invasion among resident species tend to maximize systemic colonization resistance to outsiders, when compared to resident-driven, anti-symmetric, almost anti-symmetric and random {Lambda} structures. We contend this modeling approach is a powerful new avenue to study, test and validate interaction networks and invasion topologies in diverse microbial consortia, and quantify analytically their role in colonization resistance, system function, and invasibility.

microbiology↗