Biology subjects

Su, Z.

Publications and source records attributed to Su, Z..

At least 91 records · Page 5Linked to original sources

bioRxiv2023

Manipulation of Bacterial ROS Production Leads to Self-escalating DNA Damage and Resistance-resistant Lethality for Intracellular Mycobacteria

The high prevalence of drug resistance in mycobacteria calls for antimicrobial mechanisms that suppresses the development of resistance. As a structurally conserved multi-site bio-macromolecule, DNA is presumed to be an ideal candidate for such resistance-resistant drug target. However, survey of marketed and investigational DNA interactors indicates that they are not immune to resistance development. Here, we report our strategy to achieve real resistance-resistant DNA targeting by incurring "catastrophic" DNA damage with an organoruthenium-natural product hybrid. The dual-mode DNA damage, in the form of strong tri-valent binding and concomitant oxidative modification, is achieved by manipulating of bacterias native endogenous ROS production mechanism upon lethal stress (such as DNA binding). Such self-escalating DNA damage, together with precise targeting of intracellular bacteria via vacuole fusion, thus endows the hybrids resistance-resistant lethality against mycobacteria and in vivo efficacy in animal models.

microbiology↗

bioRxiv2023

Understanding the General Principles of T Cell Engagement by Multiscale Computational Simulations

The use of bispecific antibodies as T cell engagers can bypass the normal TCR-MHC interaction, redirect the cytotoxic activity of T-cells, and lead to highly efficient tumor cell killing. However, this immunotherapy also causes significant on-target off-tumor toxicologic effects, especially when they were used to treat solid tumors. In order to avoid these adverse events, it is necessary to understand the fundamental mechanisms during the physical process of T cell engagement. We developed a multiscale computational framework to reach this goal. The framework combines simulations on the intercellular and multicellular levels. On the intercellular level, we simulated the spatial-temporal dynamics of three-body interactions among bispecific antibodies, CD3 and TAA. The derived number of intercellular bonds formed between CD3 and TAA were further transferred into the multicellular simulations as the input parameter of adhesive density between cells. Through the simulations under various molecular and cellular conditions, we were able to gain new insights of how to adopt the most appropriate strategy to maximize the drug efficacy and avoid the off-target effect. For instance, we discovered that the low antibody binding affinity resulted in the formation of large clusters at the cell-cell interface, which could be important to control the downstream signaling pathways. We also tested different molecular architectures of the bispecific antibody and suggested the existence of an optimal length in regulating the T cell engagement. Overall, the current multiscale simulations serve as a prove-of-concept study to help the future design of new biological therapeutics. SIGNIFICANCET-cell engagers are a class of anti-cancer drugs that can directly kill tumor cells by bringing T cells next to them. However, current treatments using T-cell engagers can cause serious side-effects. In order to reduce these effects, it is necessary to understand how T cells and tumor cells interact together through the connection of T-cell engagers. Unfortunately, this process is not well studied due to the limitations in current experimental techniques. We developed computational models on two different scales to simulate the physical process of T cell engagement. Our simulation results provide new insights into the general properties of T cell engagers. The new simulation methods can therefore serve as a useful tool to design novel antibodies for cancer immunotherapy.

biophysics↗

bioRxiv2023

Antisense transcription and its roles in adaption to environmental stress in E. coli

It has been reported that a highly varying proportion (1% [~] 93%) of genes in various prokaryotes have antisense RNA (asRNA) transcription. However, the extent of the pervasiveness of asRNA transcription in the well-studied E. coli K12 strain has thus far been an issue of debate. Furthermore, very little is known about the expression patterns and functions of asRNAs under various conditions. To fill these gaps, we determined the transcriptomes and proteomes of E. coli K12 at multiple time points in five culture conditions using strand-specific RNA-seq, differential RNA-seq, and quantitative mass spectrometry methods. To reduce artifacts of possible transcriptional noise, we identified asRNA using stringent criteria with biological replicate verification and transcription start sites (TSSs) information included. We identified a total of 660 asRNAs, which were generally short and largely condition-dependently transcribed. We found that the proportions of the genes which had asRNA transcription highly depended on the culture conditions and time points. We classified the transcriptional activities of the genes in six transcriptional modes according to their relative levels of asRNA to mRNA. Many genes changed their transcriptional modes at different time points of the culture conditions, and such transitions can be described in a well-defined manner. Intriguingly, the protein levels and mRNA levels of genes in the sense-only/sense-dominant mode were moderately correlated, but the same was not true for genes in the balanced/antisense-dominant mode, in which asRNAs were at a comparable or higher level to mRNAs. These observations were further validated by western blot on candidate genes, where an increase in asRNA transcription diminished gene expression in one case and enhanced it in another. These results suggest that asRNAs may directly or indirectly regulate translation by forming duplexes with cognate mRNAs. Thus, asRNAs may play an important role in the bacteriums responses to environmental changes during growth and adaption to different environments. IMPORTANCEThe cis-antisense RNA (asRNA) is a type of understudied RNA molecules in prokaryotes, which is believed to be important in regulating gene expression. Our current understanding of asRNA is constrained by inconsistent reports about its identification and properties. These discrepancies are partially caused by a lack of sufficient samples, biological replicates, and culture conditions. This study aimed to overcome these disadvantages and identified 660 putative asRNAs using integrated information from strand-specific RNA-seq, differential RNA-seq, and mass spectrometry methods. In addition, we explored the relative expression between asRNAs and sense RNAs and investigated asRNA regulated transcriptional activity changes over different culture conditions and time points. Our work strongly suggests that asRNAs may play a crucial role in bacteriums responses to environmental changes during growth and adaption to different environments.

genomics↗

bioRxiv2023

Artificial selection footprints in domestic chicken genomes

Accurate and low-cost next generation sequencing technologies make re-sequencing of large populations of a species possible. Although many studies related to artificial selection signatures of commercial and indigenous chickens have been carried out, quite a small number of genes have been found to be under selection. In this study, we re-sequenced 85 individuals of five indigenous chicken breeds with distinct traits from Yunnan, a southwest province of China. By analyzing these indigenous chickens together with 116 individuals of commercial chickens (broilers and layers) and 35 individuals of red jungle fowl, we find a substantially large number of selective sweeps and affected genes for each chicken breed using a rigorous statistic model than previously reported. We confirm most of previously identified selective sweeps and affected genes. Meanwhile the vast majority ([~]98.3%) of our identified selective sweeps overlap known chicken quantitative trait loci. Thus, our predictions are highly reliable. For each breed, we also identify candidate genes and selective sweeps that might be related to the unique traits of the chickens.

bioinformatics↗

bioRxiv2023

Structural basis for functional properties of cytochrome c oxidase

Cytochrome c oxidase (CcO) is an essential enzyme in mitochondrial and bacterial respiration. It catalyzes the four-electron reduction of molecular oxygen to water and harnesses the chemical energy to translocate four protons across biological membranes, thereby establishing the proton gradient required for ATP synthesis1. The full turnover of the CcO reaction involves an oxidative phase, in which the reduced enzyme (R) is oxidized by molecular oxygen to the metastable oxidized OH state, and a reductive phase, in which OH is reduced back to the R state. During each of the two phases, two protons are translocated across the membranes2. However, if OH is allowed to relax to the resting oxidized state (O), a redox equivalent to OH, its subsequent reduction to R is incapable of driving proton translocation2,3. How the O state structurally differs from OH remains an enigma in modern bioenergetics. Here, with resonance Raman spectroscopy and serial femtosecond X-ray crystallography (SFX)4, we show that the heme a3 iron and CuB in the active site of the O state, like those in the OH state5,6, are coordinated by a hydroxide ion and a water molecule, respectively. However, Y244, a residue covalently linked to one of the three CuB ligands and critical for the oxygen reduction chemistry, is in the neutral protonated form, which distinguishes O from OH, where Y244 is in the deprotonated tyrosinate form. These structural characteristics of O provide new insights into the proton translocation mechanism of CcO.

biophysics↗

bioRxiv2023

Underlying causes for prevalent false positives and false negatives in STARR-seq data

STARR-seq and its variants have been widely used to characterize enhancers. However, it has been reported that up to 87% of STARR peaks are located in repressive chromatins and are not functional in the tested cells. While some of the STARR peaks in repressive chromatins might be active in other cell/tissue types, some others might be false positives. Meanwhile, many active enhancers may not be identified by the current STARR-seq methods. However, the prevalence of and underlying causes for the artifacts are not fully understood. Based on predicted cis-regulatory modules (CRMs) and non-CRMs in the human genome as well as predicted active CRMs and non-active CRMs in a few human cell lines with STARR-seq data available, we reveal prevalent false positives and false negatives in STARR peaks and possible underlying causes. Our results will help design strategies to improve STARR-seq methods and interpret the results.

bioinformatics↗

bioRxiv2023

Cryo-EM-guided engineering of T-box-tRNA modules with enhanced selectivity and sensitivity in translational regulation

Riboswitches are non-coding RNA elements that play vital roles in regulating gene expression. Their specific ligand-dependent structural reorganization facilitates their use as templates for design of engineered RNA switches for therapeutics, nanotechnology and synthetic biology. T-box riboswitches bind tRNAs to sense aminoacylation and control gene expression via transcription attenuation or translation inhibition. Here we determine the cryo-EM structure of the wild-type Mycobacterium smegmatis ileS T-box in complex with its cognate tRNAIle. This structure shows a very flexible antisequestrator region that tolerates both 3-OH and 2,3-cyclic phosphate modification at the 3 end of tRNAIle. Elongation of one helical turn (11-base pair) in both the tRNA acceptor arm and T-box Stem III maintains T-box-tRNA complex formation and increases the selectivity for tRNA 3 end modification. Moreover, elongation of Stem III results in [~]6-fold tighter binding to tRNA, which leads to increased sensitivity of downstream translational regulation indicated by precedent translation. Our results demonstrate that cryo-EM can guide RNA engineering to design improved riboswitch modules for translational regulation, and potentially a variety of additional functions.

synthetic biology↗

bioRxiv2023

Real-Time Quantification of Cell Mechanics and Functions by Double Resonator Piezoelectric Cytometry -Theory and Study of Cellular Adhesion of HUVECs

Cell mechanics is closely associated with cellular structure and function. However, the inability to measure both cellular force and viscoelasticity of statistically significant number of cells noninvasively remains a challenge for quantitative characterizations of various cellular functions and practical applications. Here a double resonator piezoelectric cytometry (DRPC), using AT and BT cut quartz crystals of the same frequency and surface morphology is developed to simultaneously quantify the cells-generated forces ({Delta}S) and viscoelastic moduli (G', G'') of a population of isolated single cells or cells with different degrees of cell-cell interactions in a non-invasive and real time manner. DRPC captures the dynamic mechanical parameters {Delta}S and G', G'' during the adhesions of human umbilical vein endothelial cells (HUVECs) under different ligand densities of adhesion molecules fibronectin or Arg-Gly-Asp (RGD) modified on the gold surfaces of 9 MHz AT and BT cut quartz crystals, and different seeding densities of HUVECs. It is found that both the ligand density and cell seeding density affect the magnitudes of {Delta}S and G', G'' and their correlations are revealed for the first time by DRPC. The validity of DRPC is further verified by mechanical changes of the cells in response to treatments with cytoskeleton regulators.

biophysics↗

bioRxiv2022

Two types of locus coeruleus norepinephrine neurons drive reinforcement learning

The cerebral cortex generates flexible behavior by learning. Reinforcement learning is thought to be driven by error signals in midbrain dopamine neurons. However, they project more densely to basal ganglia than cortex, leaving open the possibility of another source of learning signals for cortex. The locus coeruleus (LC) contains most of the brains norepinephrine (NE) neurons and project broadly to cortex. We measured activity from identified mouse LC-NE neurons during a behavioral task requiring ongoing learning from reward prediction errors (RPEs). We found two types of LC-NE neurons: neurons with wide action potentials (type I) were excited by positive RPE and showed an increasing relationship with change of choice likelihood. Neurons with thin action potentials (type II) were excited by lack of reward and showed a decreasing relationship with change of choice likelihood. Silencing LC-NE neurons changed future choices, as predicted from the electrophysiological recordings and a model of how RPEs are used to guide learning. We reveal functional heterogeneity of a neuromodulatory system in the brain and show that NE inputs to cortex act as a quantitative learning signal for flexible behavior.

neuroscience↗

bioRxiv2022

Structural basis of sRNA RsmZ regulation of Pseudomonas aeruginosa virulence

Pseudomonas aeruginosa is an opportunistic human pathogen that poses threats to hospitalized immunocompromised patients 1. A non-coding small RNA (sRNA) from the repressor of secondary metabolites (Rsm) system, RsmZ, sequesters the global repressor protein RsmA to regulate downstream gene expressions that reprogram virulence repertoires associated with acute and chronic P. aeruginosa infections 2,3. Molecular insights into the full-length RsmZ architecture remain elusive, leading to the lack of understanding of RsmZ binding to RsmA and subsequent modulations of gene expressions. Here we use cryo-electron microscopy (cryo-EM) to resolve structures of the full-length RsmZ in complexes with RsmA, in which five stem-loops (SLs) and one single-stranded junction carrying the GGA binding sites in RsmZ form three pairs of clamps, each binding to a RsmA homodimer. Disruptions of the base-pairings in all stems of RsmZ significantly reduced the binding affinity to RsmA by 17-fold, which resulted in enhanced RsmA downregulation of gene expressions and phenotypes associated to both acute and chronic virulence of P. aeruginosa. Double mutations that rescued these stems of RsmZ restored the binding to RsmA by more than 5-fold, and recovered the corresponding phenotypes. Our results reveal the molecular mechanism of RsmZ regulation of P. aeruginosa virulence and suggest RsmZ as a potential target for the development of new antimicrobial agents.

microbiology↗

bioRxiv2022

Junctophilin-2 promotes cardiomyocyte survival by blocking MURF1-mediated Junctin ubiquitination and proteasome-dependent degradation

AimsJunctophilin-2 is required for the development, maturation and integrity of the t-tubule system and the gating stability of RyR2 in cardiomyocytes. This study investigated whether and how junctophilin-2 maintained junctin, a scaffold protein stabilizing RyR2, to prevent cardiomyocyte death under stress. MethodsCardiomyocytes were exposed to conditions of stress including palmitate, doxorubicin, or hypoxia/re-oxygenation. Adenoviral vectors were employed to manipulate expression of junctophilin-2 and junctin in cardiomyocytes. Molecular/cellular/biochemical analyses were conducted. ResultsDifferent conditions of stress decreased junctophilin-2 expression through aberrant autophagy and concomitantly induced a reduction of junctin protein in cardiomyocytes. Over-expression of junctophilin-2 preserved the protein levels of junctin and attenuated cytosolic Ca2+ and apoptosis in cardiomyocytes under stress. Knockdown of junctophilin-2 reproduced the detrimental phenotypes of stress in cardiomyocytes. Notably, over-expression of junctin prevented cardiomyocyte death under stress whereas knockdown of junctin offset the protective effects conferred by junctophilin-2 over-expression. Mechanistically, junctophilin-2 blocked MURF1-junctin interaction thereby preventing junctin ubiquitination and proteasome-dependent degradation. Mass spectrometry analysis identified multiple ubiquitination sites on the junctin protein and the non-ubiquitinated junctin mutant (K8A/K102A/K107A/K140A) was resistant to degradation. ConclusionsThis study uncovers an unrecognized role of junctophilin-2 in preventing junctin ubiquitination and degradation in maintaining cytosolic Ca2+ homeostasis. Both junctophilin-2 and junctin represent two new survival factors of cardiomyocytes and thus, may be new therapeutic targets for cardiac protection.

molecular biology↗

bioRxiv2022

Inferring cell diversity in single cell data using consortium-scale epigenetic data as a biological anchor for cell identity

Methods for cell clustering and gene expression from single-cell RNA sequencing (scRNA-seq) data are essential for biological interpretation of cell processes. Here we present TRIAGE-Cluster which uses genome-wide epigenetic data from diverse bio-samples to identify genes demarcating cell diversity in scRNA-seq data. TRIAGE-Cluster integrates patterns of repressive chromatin deposited across diverse cell types with weighted density estimation to determine cell type clusters in a 2D UMAP space. We then present TRIAGE-ParseR, a machine learning method that evaluates gene expression rank lists to define gene groups governing the identity and function of cell types. We demonstrate the utility of this two-step approach using atlases of in vivo and in vitro cell diversification and organogenesis. We also provide a web accessible dashboard for analysis and download of data and software. Collectively, genome-wide epigenetic repression provides a versatile strategy to define cell diversity and study gene regulation of scRNA-seq data.

bioinformatics↗

bioRxiv2022

An integrated cell barcoding and computational analysis pipeline for scalable analysis of differentiation at single-cell resolution

Pluripotent stem cells provide a scalable approach to analyse molecular regulation of cell differentiation across multiple developmental lineage trajectories. In this study, we engineered barcoded iPSCs to generate an atlas of multilineage differentiation from pluripotency, encompassing a time-course of WNT-induced differentiation perturbed using modulators of WNT, BMP, and VEGF signalling. Computational mapping of in vitro cell types to in vivo developmental lineages revealed a diversity of iPSC-derived cell types comprising mesendoderm lineage cell types including lateral plate and paraxial mesoderm, neural crest, and primitive gut. Coupling this atlas of in vitro differentiation with Summary data-based Mendelian Randomisation analysis of human complex traits, we identify the WNT-inhibitor protein TMEM88 as a putative regulator of mesendodermal cell types governing development of diverse cardiovascular and anthropometric traits. Using genetic loss of function models, we show that TMEM88 is required for differentiation of diverse endoderm and mesoderm cell lineages in vitro and that TMEM88 knockout in vivo results in a significant dysregulation of arterial blood pressure. This study provides an atlas of multilineage iPSC differentiation coupled with new molecular, computational, and statistical genetic tools to dissect genetic determinants of mammalian developmental physiology.

genomics↗

bioRxiv2022

Dissociated amplitude and phase effects of alpha oscillation in a nested structure of rhythm- and sequence-based temporal expectation

The human brain can utilize various information to form temporal expectation and optimize perceptual performance. Here we show dissociated amplitude and phase effects of pre-stimulus alpha oscillation in a nested structure of rhythm- and sequence-based expectation. A visual stream of rhythmic stimuli was presented in a fixed sequence such that their temporal positions could be predicted by either the low-frequency rhythm, the sequence, or the combination. The behavioral modelling indicated that rhythmic and sequence information additively led to increased accumulation of sensory evidence and alleviated threshold for the perceptual discrimination of the expected stimulus. The electroencephalographical (EEG) results showed that the alpha amplitude was dominated by rhythmic information, with the amplitude fluctuating in the same frequency of the oscillation entrained by the rhythmic information (i.e., phase-amplitude coupling). The alpha phase, however, was affected by both rhythmic and sequence information. Importantly, rhythm-based expectation improved the perceptual performance by decreasing the alpha amplitude, whereas sequence-based expectation did not further decrease the amplitude on top of rhythm-based expectation. Moreover, rhythm-based and sequence-based expectation collaboratively improved the perceptual performance by biasing the alpha oscillation toward the optimal phase. Our findings suggested flexible coordination of multiscale brain oscillations in dealing with a complex environment.

neuroscience↗

bioRxiv2022

The role of proton in a eukaryotic zinc transporter

Zinc transporter 8 (ZnT8) is mainly expressed in pancreatic islet {beta} cells and is responsible for H+-coupled uptake (antiport) of Zn2+ into the lumen of insulin secretory granules. Structures of human ZnT8 and its prokaryotic homolog YiiP have provided structural basis for constructing a plausible transport cycle for Zn2+. However, the mechanistic role that protons play in the transport process remains unclear. Here we present a lumen-facing cryo-EM structure of ZnT8 from Xenopus tropicalis (xtZnT8) in the presence of Zn2+ at a luminal pH (5.5). Compared to a Zn2+-bound xtZnT8 structure at a cytosolic pH (7.5), the low-pH structure displays an empty transmembrane Zn2+-binding site with a disrupted coordination geometry. Combined with a Zn2+-binding assay our data suggest that protons may disrupt Zn2+ coordination at the transmembrane Zn2+-binding site in the lumen-facing state, thus facilitating Zn2+ release from ZnT8 into the lumen.

biochemistry↗

bioRxiv2022

Wild-type allele of TaHRC suppresses calcium-mediated plant immune response by hijacking TaCAXIP4 to trigger FHB susceptibility in wheat

Fusarium head blight (FHB) is one of the most destructive diseases of wheat worldwide. Epidemics of FHB cause a serious reduction in grain yield and quality of wheat and result in significant economic losses to wheat producers. Recently, we have cloned a histidine-rich calcium-binding protein gene (TaHRC) as the causal gene for Fhb1 and demonstrated that the wild-type allele of TaHRC conditions FHB susceptibility and a large deletion including the start codon resulted in FHB resistance. However, the molecular mechanisms on how TaHRC regulating FHB susceptibility remains unknown. In this study, we conducted yeast two-hybrid screening (Y2H) against the wheat cDNA expression libraries using TaHRC as bait and identified a cation exchanger (CAX)-interacting protein 4 (TaCAXIP4) as the candidate protein that interacts with TaHRC to affect calcium transport activity. The strong interaction was further confirmed by Bimolecular fluorescence complementation (BiFC) assays. Using gene editing, we edited three different sites (one before and one within and one after the NLS domain) of TaHRC in a susceptible wheat cultivar Bobwhite using the CRISPR/Cas9 gene editing technology and demonstrated the N-terminus carrying NLS domain of TaHRC plays a critical role for the interaction and conditions TaHRC function on FHB susceptibility. We determined that the interaction between TaCAXIP4 and TaHRC occurs in the nuclei of cells by subcellular colocalization assay. Intriguingly, we found TaHRC can sequester TaCAXIP4 to suppress the Ca2+ transporting activity of TaCAX1 (a H+/Ca2+ antiporter) through yeast calcium suppression assay and suggested wild-type TaHRC may hijack TaCAXIP4 to suppresses calcium-mediated plant immune response during Fusarium infection in wheat. Furthermore, we performed the reactive oxygen species (ROS) assays and further showed that TaHRC might suppress the chitin-triggered plant immune responses during Fusarium infection by sequestering TaCAXIP4 to trigger FHB susceptibility, which facilitates the pathogen spread within a wheat spike. This work provides first line of evidence to support wild type Fhb1 is a susceptible gene and how Fhb1 wild type allele regulate FHB susceptibility.

plant biology↗

bioRxiv2022

Processing UMI Datasets at High Accuracy and Efficiency with the Sentieon ctDNA Analysis Pipeline

Liquid biopsy enables identification of low allele frequency (AF) tumor variants and novel clinical applications such as minimum residual disease (MRD) monitoring. However, challenges remain, primarily due to limited sample volume and low read count of low-AF variants. Because of the low AFs, some clinically significant variants are difficult to distinguish from errors introduced by PCR amplification and sequencing. Unique Molecular Identifiers (UMIs) have been developed to further reduce base error rates and improve the variant calling accuracy, which enables better discrimination between background errors and real somatic variants. While multiple UMI-aware ctDNA analysis pipelines have been published and adopted, their accuracy and runtime efficiency could be improved. In this study, we present the Sentieon ctDNA pipeline, a fast and accurate solution for small somatic variant calling from ctDNA sequencing data. The pipeline consists of four core modules: alignment, consensus generation, variant calling, and variant filtering. We benchmarked the ctDNA pipeline using both simulated and real datasets, and found that the Sentieon ctDNA pipeline is more accurate than alternatives.

bioinformatics↗

bioRxiv2022

DeepTracer ID: De Novo Protein Identification from Cryo-EM Maps

The recent revolution in cryo-electron microscopy has made it possible to determine macromolecular structures directly from cell extracts. However, identifying the correct protein from the cryo-EM map is still challenging and often needs additional sequence information from other techniques, such as tandem mass spectrometry and/or bioinformatics. Here, we present DeepTracer-ID, a server-based approach to identify the candidate protein in a user-provided organism de novo from a cryo-EM map, without the need for additional information. Our method first uses DeepTracer to generate a protein backbone model that best represents the cryo-EM map, and this model is then searched against the library of AlphaFold2 predictions for all proteins in the given organism. This method is highly accurate and robust: in all 13 experimental maps tested blindly, DeepTracer-ID identified the correct proteins as the top candidates. Eight of the maps were of known structures, while the other five unpublished maps were validated by prior protein annotation and careful inspection of the model refined into the map. The program also showed promising results for both homomeric and heteromeric protein complexes. This platform is possible because of the recent breakthroughs in large-scale protein 3D structure prediction. Statement of SignificanceWhile it has now become routine for cryo-EM maps of proteins to reach a near-atomic resolution, potentially allowing for reliable atomic models to be built, there are a growing number of instances where the protein identity may not be known. Without knowing the protein sequence, it is impossible to build an atomic model. DeepTracer-ID is a server-based approach to surmount this problem by identifying the proteins in a given organism that are found in the cryo-EM map. A free web service for global academic access is provided.

biophysics↗