Biology subjects

Ray, D.

Publications and source records attributed to Ray, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Probing the role of macromolecular crowding in cell volume regulation using fluorescence anisotropy

Cytoplasmic macromolecular crowding (MMC) influences multiple cellular functions. Using fluorescence anisotropy of EGFP, we explore the homeostasis of MMC in the cytoplasm and its role in cell volume regulation. Individual cells of different lineages maintain a distinctly unique average cytoplasmic MMC for considerably long durations. Despite diffusion, actin cytoskeleton facilitates spatially heterogeneous MMC in the cytoplasm. While hypertonic-stress triggers regulatory volume increase (RVI), other methods of increasing cytoplasmic MMC fail to start RVI, suggesting that cells lack capabilities for MMC homeostasis. During spreading or microtubule-depolymerized state, cells neglect changes in cytoplasmic MMC to undergo volume regulation. Inhibition of TNFR1 increases the membrane tension and deprives cells of their ability to undergo volume regulation. Current understanding contemplates that cytoplasmic MMC, the mechanical state of the plasma membrane or the actin cytoskeleton, could be sensors for cell volume regulation. Our observations establish the irrelevance of cytoplasmic MMC and the significance of plasma membrane tension in setting off the cell volume regulation machinery.

cell biology↗

bioRxiv2022

Probabilistic Brain Extraction in MR Images via Conditional Generative Adversarial Networks

Brain extraction, which refers to the task of segmenting brain tissue in an MR image of a subject, forms an essential first step for many quantitative neuroimaging applications. These include quantifying grey and white matter volumes, monitoring neurological diseases like multiple sclerosis (MS) and Alzheimers disease, and estimating brain atrophy. Over the years several algorithms that automate brain extraction have been proposed. More recently, novel image-to-image deep learning methods have been implemented for this task, and have demonstrated significant gains in accuracy and robustness. However, to our knowledge, none of these algorithms account for the uncertainty that is inherent in brain extraction. Motivated by this, we propose a novel, probabilistic deep learning algorithm for brain extraction that recasts this task as a Bayesian inference problem, and then utilizes a conditional generative adversarial network (cGAN) to solve it. The input to the generator network is an MR image of the head and the output is a collection of images of the brain that are drawn from a probability density conditioned on the input image. These images are used to generate a pixel-wise mean image, which serves as the best guess for an image of the brain, and a pixel-wise standard deviation image, which quantifies the uncertainty in the prediction. We test this algorithm on head MR images of fifty subjects and demonstrate that it is more accurate than a commonly used brain extraction tool, and that its performance compares well with the current state of the art in deep learning algorithms. We also demonstrate the utility of the estimates of uncertainty generated by the algorithm.

bioengineering↗

bioRxiv2021

Pectin self-assembly and its disruption by water: Insights into plant cell wall mechanics

Plant cell walls undergo multiple cycles of dehydration and rehydration during their life. Calcium crosslinked low methoxy pectin is a major constituent of plant cell walls. Understanding the dehydration-rehydration behavior of pectin gels may shed light on the water transport and mechanics of plant cells. In this work, we report the contributions of microstructure to the mechanics of pectin-Ca gels subjected to different extents of dehydration and subsequent rehydration. This is investigated using a pectin gel composition that forms egg-box bundles, a characteristic feature of the microstructure of low methoxy pectin-Ca gels. Large Amplitude Oscillatory Shear (LAOS) rheology along with Small Angle Neutron Scattering and Near Infrared (NIR) spectroscopy on pectin gels are used to elucidate the mechanical and microstructural changes during dehydration-rehydration cycles. As the extent of dehydration increase, the reswelling ability, strain-stiffening behavior and the yield strain decreases. These effects are more prominent at faster rates of dehydration and are not completely reversible upon rehydration to the initial undried state. Microstructural changes due to the aggregation of egg-box bundles and single chains and the associated changes in the water configurations lead to these irreversible changes.

plant biology↗

bioRxiv2021

Looking from the top: enhanced top-down sensorimotor processing in somatic anxiety

Functional neuroimaging research on anxiety has traditionally focused on brain networks associated with the psychological aspects of anxiety. Here, instead, we target the somatic aspects of anxiety. Motivated by the growing appreciation that top-down cortical processing plays a crucial role in perception and action, we used resting-state functional MRI data from the Human Connectome Project and Dynamic Causal Modeling (DCM) to characterize effective connectivity among hierarchically organized regions in the exteroceptive, interoceptive, and motor cortices. In people with high (fear-related) somatic arousal, top-down effective connectivity was enhanced in all three networks: an observation that corroborates well with the phenomenology of anxiety. The anxiety-associated changes in connectivity were sufficiently reliable to predict whether a new participant has mild or severe somatic anxiety. Interestingly, the increase in top-down connections to sensorimotor cortex were not associated with fear affect scores, thus establishing the (relative) dissociation between somatic and cognitive dimensions of anxiety. Overall, enhanced top-down effective connectivity in sensorimotor cortices emerges as a promising and quantifiable candidate marker of trait somatic anxiety.

neuroscience↗

bioRxiv2021

Benchmarking statistical methods for analyzing parent-child dyads in genetic association studies

Genetic association studies of child health outcomes often employ family-based designs. One of the most popular family-based designs is the case-parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population-based study designs (e.g., case-control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother-child dyads. While some statistical methods for analyzing parent-child dyad data (most commonly involving mother-child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case-mother dyads vs. case-mother/control-mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome-wide data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case-parent trios and dyads together. We apply these methods on genotyped and imputed data from multi-ethnic mother-child pairs only, case-parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads.

genetics↗

bioRxiv2021

The X-linked splicing regulator MBNL3 has been co-opted to restrict placental growth in eutherians

The eutherian placenta is a major site for parental genetic conflict. Here, we identify the X-linked Mbnl3 gene as a novel player in this dispute. Mbnl3 belongs to an RNA binding protein family whose members regulate alternative splicing and other aspects of RNA metabolism in association with cellular differentiation. We find that, in eutherians, Mbnl3 has become specifically expressed in placenta and has undergone accelerated sequence evolution leading to changes in its RNA binding specificities. Although its molecular roles are partly redundant with those of Mbnl2, Mbnl3 has also acquired novel biological functions. In particular, whereas Mbnl2;Mbnl3 double knockout mice display severe placental maturation defects leading to strong histological and functional abnormalities, Mbnl3 knockout alone results in increased placental growth and favors placental and fetal resource allocation during limiting conditions.

evolutionary biology↗

bioRxiv2021

Mutations in SARS-CoV-2 Variants Modulate the Microscopic Dynamics of Neutralizing Antibodies

Monoclonal antibodies are emerging as a viable treatment for the coronavirus disease 19 (COVID-19). However, newly evolved variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can reduce the efficacy of currently available antibodies and can diminish vaccine-induced immunity. Here, we demonstrate that the microscopic dynamics of neutralizing monoclonal antibodies can be profoundly modified by the mutations present in the spike proteins of the SARS-COV-2 variants currently circulating in the world population. The dynamical perturbations within the antibody structure, which alter the thermodynamics of antigen recognition, are diverse and can depend both on the nature of the antibody and on the spatial location of the spike mutation. The correlation between the motion of the antibody and that of the spike receptor binding domain (RBD) can also be changed, modulating binding affinity. Using protein-graph-connectivity networks, we delineated the mutant-induced modifications in the information-flow along allosteric pathway throughout the antibody. Changes in the collective dynamics were spatially distributed both locally and across long-range distances within the antibody. On the receptor side, we identified an anchor-like structural element that prevents the detachment of the antibodies; individual mutations there can significantly affect the antibody binding propensity. Our study provides insight into how virus neutralization by monoclonal antibodies can be impacted by local mutations in the epitope via a change in dynamics. This realization adds a new layer of sophistication to the efforts for rational design of monoclonal antibodies against new variants of SARS-CoV2, taking the allostery in the antibody into consideration.

biophysics↗

bioRxiv2021

Markovian Weighted Ensemble Milestoning (M-WEM): Long-time Kinetics from Short Trajectories

We introduce a rare-event sampling scheme, named Markovian Weighted Ensemble Milestoning (M-WEM), which inlays a weighted ensemble framework within a Markovian milestoning theory to efficiently calculate thermodynamic and kinetic properties of long-timescale biomolecular processes from short atomistic molecular dynamics simulations. M-WEM is tested on the Muller-Brown potential model, the conformational switching in alanine dipeptide, and the millisecond timescale protein-ligand unbinding in a trypsin-benzamidine complex. Not only can M-WEM predict the kinetics of these processes with quantitative accuracy, but it also allows for a scheme to reconstruct a multidimensional free energy landscape along additional degrees of freedom which are not part of the milestoning progress coordinate. For the ligand-receptor system, the experimental residence time, association and dissociation kinetics, and binding free energy could be reproduced using M-WEM within a simulation time of a few hundreds of nanoseconds, which is a fraction of the computational cost of other currently available methods, and close to four orders of magnitude less than the experimental residence time. Due to the high accuracy and low computational cost, the M-WEM approach can find potential application in kinetics and free-energy based computational drug design.

biophysics↗

bioRxiv2021

Altered Effective Connectivity in Sensorimotor Cortices: a Novel Signature of Severity and Clinical Course in Depression

Functional neuroimaging research on depression has traditionally targeted neural networks associated with the psychological aspects of depression. In this study, instead, we focus on alterations of sensorimotor function in depression. We used resting-state functional MRI data and Dynamic Causal Modeling (DCM) to assess the hypothesis that depression is associated with aberrant effective connectivity within and between key regions in the sensorimotor hierarchy. Using hierarchical modeling of between-subject effects in DCM with Parametric Empirical Bayes we first established the architecture of effective connectivity in sensorimotor cortices. We found that in (interoceptive and exteroceptive) sensory cortices across participants, the backward connections are predominantly inhibitory whereas the forward connections are mainly excitatory in nature. In motor cortices these parities were reversed. With increasing depression severity, these patterns are depreciated in exteroceptive and motor cortices and augmented in the interoceptive cortex: an observation that speaks to depressive symptomatology. We established the robustness of these results in a leave-one-out cross validation analysis and by reproducing the main results in a follow-up dataset. Interestingly, with (non-pharmacological) treatment, depression associated changes in backward and forward effective connectivity partially reverted to group mean levels. Overall, altered effective connectivity in sensorimotor cortices emerges as a promising and quantifiable candidate marker of depression severity and treatment response. Significance StatementResearch into neurobiology of depression primarily focuses on its complex psychological aspects. Here, we propose an alternative approach and target sensorimotor alterations - a prominent but often neglected feature of depression. We demonstrated using resting-state fMRI data and computational modelling that top-down and bottom-up information flow in sensory and motor cortices is altered with increasing depression severity in a way that is consistent with depression symptoms. Depression associated changes were found to be consistent across sessions, amenable to treatment and of effect size sufficiently large to predict whether somebody has mild or severe depression. These results pave the way for a new avenue of research into the neural underpinnings of mental health conditions.

neuroscience↗

bioRxiv2020

Distant Residues Modulate the Conformational Opening in SARS-CoV-2 Spike Protein

Infection by SARS-CoV-2 involves the attachment of the receptor binding domain (RBD) of its spike proteins to the ACE2 receptors on the peripheral membrane of host cells. Binding is initiated by a down-to-up conformational change in the spike protein, the change that presents the RBD to the receptor. To date, computational and experimental studies that search for therapeutics have concentrated, for good reason, on the RBD. However, the RBD region is highly prone to mutations, and is therefore a hotspot for drug resistance. In contrast, we here focus on the correlations between the RBD and residues distant to it in the spike protein. This allows for a deeper understanding of the underlying molecular recognition events and prediction of the highest-effect key mutations in distant, allosteric sites, with implications for therapeutics. Also, these sites can appear in emerging mutants with possibly higher transmissibility and virulence, and pre-identifying them can give clues for designing pancoronavirus vaccines against future outbreaks. Our model, based on time-lagged independent component analysis (tICA) and protein graph connectivity network, is able to identify multiple residues that exhibit long-distance coupling with the RBD opening. Residues involved in the most ubiquitous D614G mutation and the A570D mutation of the highly contagious UK SARS-CoV-2 variant are predicted ab-initio from our model. Conversely, broad spectrum therapeutics like drugs and monoclonal antibodies can target these key distant-but-conserved regions of the spike protein. Significance StatementThe novel coronavirus (SARS-CoV-2) pandemic resulted in the largest public health crisis in recent times. Significant drug design effort against SARS-CoV-2 is focused on the receptor binding domain (RBD) of the spike protein, although this region is highly prone to mutations causing therapeutic resistance. We applied deep data analysis methods on all-atom molecular dynamics simulations to identify key non-RBD residues that play a crucial role in spike-receptor binding and infection. textcol-orredBecause the non-RBD residues are typically conserved across multiple coronaviruses, they can be targeted by broad spectrum antibodies and drugs to treat infections from new strains that might appear during future epidemics.

biophysics↗

bioRxiv2020

Homeostatic brain network mechanisms facilitate perceptual binding of audio-visual speech

Speech perception requires the binding of spatiotemporally disjoint auditory-visual cues. The corresponding brain network-level information processing can be characterized by two complementary mechanisms: functional segregation which refers to the localization of processing in either isolated or distributed modules across the brain, and integration which pertains to cooperation among relevant functional modules. Here, we demonstrate using fMRI recordings that subjective perceptual experience of multisensory speech stimuli, real and illusory, are represented in differential states of segregation-integration. We controlled the inter-subject variability of illusory/cross-modal perception parametrically, by introducing temporal lags in the incongruent auditory-visual articulations of speech sounds within the McGurk paradigm. The states of segregation-integration balance were captured using two alternative computational approaches. First, the module responsible for cross-modal binding of sensory signals defined as the perceptual binding network (PBN) was identified using standardized parametric statistical approaches and their temporal correlations with all other brain areas were computed. With increasing illusory perception, the majority of the nodes of PBN showed decreased cooperation with the rest of the brain, reflecting states of high segregation but reduced global integration. Second, using graph theoretic measures, the altered patterns of segregation-integration were cross-validated.

neuroscience↗

bioRxiv2020

A Powerful Method for Pleiotropic Analysis under Composite Null Hypothesis Identifies Novel Shared Loci Between Type 2 Diabetes and Prostate Cancer

SO_SCPLOWUMMARYC_SCPLOWThere is increasing evidence that pleiotropy, the association of multiple traits with the same genetic variants/loci, is a very common phenomenon. Cross-phenotype association tests are often used to jointly analyze multiple traits from a GWAS. The underlying methods, however, are often designed to test the global null hypothesis that there is no association of a genetic variant with any of the traits, the rejection of which does not implicate pleiotropy. In this article, we propose a new statistical approach, PLACO, for specifically detecting pleiotropic loci between two traits by considering an underlying composite null hypothesis that a variant is associated with none or only one of the traits. We propose testing the null hypothesis based on the product of the Z-statistics of the SNPs across two studies and derive a null distribution of the test statistic in the form of a mixture distribution that allows for fractions of SNPs to be associated with none or only one of the traits. We borrow approaches from the statistical literature on mediation analysis that allow asymptotic approximation of the null distribution avoiding estimation of nuisance parameters related to mixture proportions and variance components. Simulation studies demonstrate that the proposed method can maintain type I error and can achieve major power gain over alternative simpler methods that are typically used for testing pleiotropy. PLACO allows correlation in summary statistics between studies that may arise due to sharing of controls between disease traits. Application of PLACO to publicly available summary data from two large case-control GWAS of Type 2 Diabetes and of Prostate Cancer implicated a number of novel shared genetic regions near ZBTB38 (3q23), RGS17 (6q25.3), HAUS6 (9p22.1), UBAP2 (9p13.3), RAPSN (11p11.2), AKAP6 (14q12), KNL1 (15q15) and ZNF236 (18q23).

genetics↗

bioRxiv2020

Mutant EGFR is a preferred SMURF2 substrate of ubiquitination: role in enhanced receptor stability and TKI sensitivity

We previously reported that differential protein degradation of TKI-sensitive [L858R, del(E746-A750)] and resistant (T790M) epidermal growth factor receptor (EGFR) mutants upon erlotinib treatment correlates with drug sensitivity. However, the molecular mechanism remains unclear. We also reported SMAD ubiquitination regulatory factor 2 (SMURF2) ligase activity is important in stabilizing EGFR. Here, using in vitro and in vivo ubiquitination assays, mass spectrometry, and super-resolution microscopy, we show SMURF2-EGFR functional interaction is critical in receptor stability and TKI sensitivity. We found that L858R/T790M EGFR is a preferred substrate of SMURF2-UBCH5 (an E3-E2) complex-mediated K63-linked polyubiquitination, which preferentially stabilizes mutant receptor. We identified four lysine (K) residues (K721, 846, 1037 and 1164) as the sites of ubiquitination and replacement of K to acetylation-mimicking asparagine (Q) at K1037 position in L858R/T790M background converts the stable protein sensitive to erlotinib-induced degradation. Using STochastic Optical Reconstruction Microscopy (STORM) imaging, we show that SMURF2 presence allows longer membrane retention of activated EGFR upon EGF treatment, whereas, siRNA-mediated SMURF2 knockdown fastens receptor endocytosis and lysosome enrichment. In an erlotinib-sensitive PC9 cells, SMURF2 overexpression increased EGFR levels with improved erlotinib tolerance, whereas, SMURF2 knockdown decreased EGFR steady state levels in NCI-H1975 and PC9-AR cells to overcome erlotinib and AZD-9291 resistance respectively. Additionally, by genetically altering the SMURF2-UBCH5 complex formation destabilized EGFR. Together, we propose that SMURF2-mediated preferential polyubiquitination of L858R/T790M EGFR may be competing with acetylation-mediated receptor internalization to provide enhanced receptor stability and that disruption of the E3-E2 complex may be an attractive alternate to overcome TKI resistance.

cancer biology↗

bioRxiv2020

RAS activation via CRLF2 signaling is a widespread mechanism in Down syndrome acute lymphoblastic leukemia regardless of RAS mutations

BackgroundDown syndrome acute lymphoblastic leukemia (DS-ALL) is characterized by the high frequency of CRLF2-rearrangements, JAK2-mutations, or RAS-pathway mutations. Intriguingly, JAK2 and RAS mutations are mutually exclusive in leukemic sub-clones, causing dichotomy in therapeutic target choices. ResultsHere we show that in primary leukemic cells from DS-ALL, in the absence of RAS-mutations, wild-type (wt)RAS is active, and/or can be induced by the physiological ligand TSLP of the transmembrane-receptor CRLF2. We show active/inducible RAS in 14/20 (70%) of primary DS-ALL samples analyzed, 8 of which had no RAS-mutations, but 75% of those had either mutated or hyperphosphorylated JAK2. No wtRAS cases with mutated/hyperphosphorylated JAK2 were observed that lacked activated RAS protein. We prove in a cell model that elevated CRLF2 in combination with constitutionally active JAK2 is sufficient to activate wtRAS. We show that TSLP boosts the direct binding of active PTPN11 to wtRAS. Pre-inhibition of RAS or PTPN11, but not of PI3K or JAK signaling, prevented TSLP-induced RAS-GTP boost. Using multivariate-clustering based on RAS-activity/inducibility we show significant separation between standard-risk and high-risk DS-ALL groups. Cox proportional-hazards model showed protein-activity (but not mutation status) as independently predictive of outcome. ConclusionsOur data indicate that RAS protein activity levels (and not JAK2/RAS mutation profiles), are predictive of outcome. Importantly, our data suggest that inhibition of RAS and direct RAS-pathway components should be combined with PI3K/mTOR and/or JAK2 inhibitors for high-risk cases. Therapeutically this is relevant for >75% of DS-ALL and our additional data suggest that it warrants further investigation in high-risk non-DS-ALL.

cancer biology↗

bioRxiv2020

Free Energy Landscape and Conformational Kinetics of Hoogsteen Base-Pairing in DNA vs RNA

Genetic information is encoded in the DNA double helix which, in its physiological milieu, is characterized by the iconical Watson-Crick nucleobase pairing. Recent NMR relaxation experiments revealed the transient presence of an alternative, Hoogsteen base pairing pattern in naked DNA duplexes and estimated its relative stability and lifetime. In contrast, HG transitions in RNA were not observed. Understanding Hoogsteen (HG) base pairing is important because the underlying "breathing" can modulate significantly DNA/RNA recognition by proteins. However, a detailed mechanistic insight into the transition pathways and kinetics is still missing. We performed enhanced sampling simulation (with combined metadynamics and adaptive force bias method) and Markov State modeling to obtain accurate free energy, kinetics and the intermediates in the transition pathway between WC and HG base pair for both naked B-DNA and A-RNA duplexes. The Markov state model constructed from our unbiased MD simulation data revealed previously unknown complex extra-helical intermediates in this seemingly simple process of base pair conformation switching in B-DNA. Extending our calculation to A-RNA, for which HG base pair is not observed experimentally, resulted in relatively unstable single hydrogen bonded distorted Hoogsteen like base pair. Unlike B-DNA the transition pathway primarily involved base paired and intra-helical intermediates with transition timescales much higher than that of B-DNA. The seemingly obvious flip-over reaction coordinate, i.e., the glycosidic torsion angle is unable to resolve the intermediates; so a multidimensional picture, involving backbone dihedral angles and distance between atoms participating in hydrogen bonds, is required to gain insight into the molecular mechanism. SIGNIFICANCEFormation of unconventional Hoogsteen (HG) base pairing is an important problem in DNA biophysics owing to its key role in facilitating the binding of DNA repairing enzymes, proteins and drugs to damaged DNA. X-ray crystallography and NMR relaxation experiments revealed the presence of HG base pair in naked DNA duplex and protein-DNA complex but no HG base pair was observed in RNA. Molecular dynamics simulations could reproduce the experimental free energy cost of HG base pairing in DNA although a detailed mechanistic insight is still missing. We performed enhanced sampling simulation and Markov state modeling to obtain accurate free energy, kinetics and the intermediates in the transition pathway between WC and HG base pair for both B-DNA and A-RNA.

biophysics↗

bioRxiv2019

Parallel Streams to Interconnected Networks: Organization and Reorganization of Cortical Processing During Visual Perception and Action

Visual dual stream theory posits that two distinct neural pathways of specific functional significance originate from primary visual areas and reach the inferior temporal (ventral) and posterior parietal areas (dorsal). However, there are several unresolved questions concerning the fundamental aspects of this theory. For example, is the functional dissociation between ventral and dorsal stream driven by features in input stimuli or is it driven by categorical differences between visuo-perceptual and visuo-motor functions? Is the dual stream rigid or flexible? What is the nature of the interactions between two streams? We addressed these questions using fMRI recordings on healthy human volunteers and employing stimuli and tasks that can tease out the divergence between visuo-perceptual and visuo-motor models of dual stream theory. fMRI scans were repeated after seven practice sessions that were conducted in a non-MRI environment to investigate the effects of neuroplasticity. Brain activation analysis supports an input-based functional dissociation and existence of context-dependent neuroplasticity in dual stream areas. Intriguingly, premotor cortex activation was observed in the position perception task and distributed deactivated regions were observed in all perception tasks thus, warranting a network level analysis. Dynamic causal modelling (DCM) analysis incorporating activated and deactivated brain areas during perception tasks indicates that the brain dynamics during visual perception and actions could be interpreted within the framework of predictive coding. Effectively, the network level findings point towards the existence of more intricate context-driven functional networks selective of "what" and "where" information rather than segregated streams of processing along ventral and dorsal brain regions.

neuroscience↗

bioRxiv2018

Exome sequencing identifies high impact trait-associated alleles enriched in Finns

As yet undiscovered rare variants are hypothesized to substantially influence an individuals risk for common diseases and traits, but sequencing studies aiming to identify such variants have generally been underpowered. In isolated populations that have expanded rapidly after a population bottleneck, deleterious alleles that passed through the bottleneck may be maintained at much higher frequencies than in other populations. In an exome sequencing study of nearly 20,000 cohort participants from northern and eastern Finnish populations that exemplify this phenomenon, most novel trait-associated deleterious variants displayed frequencies 10-173 times higher than in other European populations. These enriched alleles underlie 30 novel associations with 20 disease-related quantitative traits and demonstrate a geographical clustering equivalent to that of Mendelian disease mutations characteristic of the Finnish population. Sequencing studies in populations without this unique history would require hundreds of thousands to millions of participants for comparable power.

genomics↗

bioRxiv2018

Electrospray sample injection for single-particle imaging with X-ray lasers

The possibility of imaging single proteins constitutes an exciting challenge for X-ray lasers. Despite encouraging results on large particles, imaging small particles has proven to be difficult for two reasons: not quite high enough pulse intensity from currently available X-ray lasers and, as we demonstrate here, contamination of the aerosolised molecules by non-volatile contaminants in the solution. The amount of contamination on the sample depends on the initial droplet-size during aerosolisation. Here we show that with our electrospray injector we can decrease the size of aerosol droplets and demonstrate virtually contaminant-free sample delivery of organelles, small virions, and proteins. The results presented here, together with the increased performance of next generation X-ray lasers, constitute an important stepping stone towards the ultimate goal of protein structure determination from imaging at room temperature and high temporal resolution.

biophysics↗