Biology subjects

Zhang, G.

Publications and source records attributed to Zhang, G..

At least 325 records · Page 18Linked to original sources

bioRxiv2021

A positively Tuned Voltage Indicator Reveals Electrical Correlates of Calcium Activity in the Brain

Neuronal spiking activity is routinely recorded using genetically encoded calcium indicators (GECIs), but calcium imaging is limited in temporal resolution and does not report subthreshold voltage changes. Genetically encoded voltage indicators (GEVIs) offer better temporal resolution and subthreshold sensitivity, but spike detection with fast GEVIs has required specialized imaging equipment. Here, we report the ASAP4 subfamily of genetically encoded voltage indicators (GEVIs) that brighten in response to membrane depolarization, inverting the fluorescence-voltage relationship of previous ASAP GEVIs. Two variants, ASAP4b and ASAP4e, feature 128% and 178% fluorescence increases over 100-mV of depolarization, respectively, facilitating spike detection in single trials in vivo with standard 1 and 2-photon imaging systems. Simultaneous voltage and calcium imaging confirms improved temporal resolution and spike discernment by ASAP4 GEVIs. Thus, positively tuned ASAP4 voltage indicators enable recording of neuronal spiking activity using similar equipment as calcium imaging, while providing higher temporal resolution. One Sentence SummaryUpward ASAPs increase detection capability of GEVIs in vivo.

neuroscience↗

bioRxiv2021

Severe fever with thrombocytopenia syndrome virus and parthenogenetic Asian longhorned tick Haemaphysalis longicornis (Acari: Ixodidae)

Severe fever with thrombocytopenia syndrome virus (SFTSV) is spreading rapidly in Asia. It is transmitted by Haemaphysalis longicornis (Asian longhorned tick, ALT), which has both parthenogenetically and sexually reproducing populations. Parthenogenetic populations were found in at least 15 provinces in China and strongly correlated with the distribution of SFTS. The distribution of SFTS cases was however poorly correlated with the distribution of populations of bisexual ALTs. Phylogeographic analysis suggested that the parthenogenetic population spread much faster than bisexual population because colonization is independent of sexual reproduction. A higher proportion of parthenogenetic ALTs were collected from migratory birds captured at an SFTS endemic area, implicating the contribution to the long-range movement of ALTs in China. The SFTSV susceptibility of parthenogenetic females was like that of bisexual females under laboratory conditions. These results suggest that parthenogenetic ALT, probably transported by migratory birds, play a major role in the rapid spread of SFTSV. Article Summary LineThe parthenogenetic population of Asian longhorned tick is broadly distributed in China and plays a major role in the long-distance spread of SFTSV and perhaps future invasion of countries outside of Asia.

evolutionary biology↗

bioRxiv2021

Local adaptation and spatiotemporal patterns of genetic diversity revealed by repeated sampling of Caenorhabditis elegans across the Hawaiian Islands

The nematode Caenorhabditis elegans is among the most widely studied organisms, but relatively little is known about its natural ecology. Wild C. elegans have been isolated from both temperate and tropical climates, where they feed on bacteria associated with decomposing plant material. Genetic diversity is low across much of the globe but high in the Hawaiian Islands and across the Pacific Rim. The high genetic diversity found there suggests that: (1) the origin of the species lies in Hawaii or the surrounding Pacific Rim; and (2) the ancestral niche of the species is likely similar to the Hawaiian niche. A recent study of the Hawaiian niche found that genetically distinct groups appeared to correlate with elevation and temperature, but the study had a limited sample size. To better characterize the niche and genetic diversity of C. elegans on the Hawaiian Islands and to explore how genetic diversity might be influenced by local adaptation, we repeatedly sampled nematodes over a three-year period, measured various environmental parameters at each sampling site, and whole-genome sequenced the C. elegans isolates that we identified. We found that the typical Hawaiian C. elegans niche is moderately moist native forests at high elevations (500 to 1500 meters) where temperatures are cool (15 to 20{degrees}C). We measured levels of genetic diversity and differentiation among Hawaiian strains and found evidence of seven genetically distinct groups distributed across the islands. Then, we scanned these genomes for signatures of local adaptation and identified 18 distinct regions that overlap with hyperdivergent regions, which are likely maintained by balancing selection and enriched for genes related to environmental sensing, xenobiotic detoxification, and pathogen resistance. These results provide strong evidence of local adaptation among Hawaiian C. elegans and a possible genetic basis for this adaptation.

ecology↗

bioRxiv2021

DeepUMQA: Ultrafast Shape Recognition-based Protein Model Quality Assessment using Deep Learning

MotivationProtein model quality assessment is a key component of protein structure prediction. In recent research, the voxelization feature was used to characterize the local structural information of residues, but it may be insufficient for describing residue-level topological information. Design features that can further reflect residue-level topology when combined with deep learning methods are therefore crucial to improve the performance of model quality assessment. ResultsWe developed a deep-learning method, DeepUMQA, based on Ultrafast Shape Recognition (USR) for the residue-level single-model quality assessment. In the framework of the deep residual neural network, the residue-level USR feature was introduced to describe the topological relationship between the residue and overall structure by calculating the first moment of a set of residue distance sets and then combined with 1D, 2D, and voxelization features to assess the quality of the model. Experimental results on test datasets of CASP13, CASP14, and CAMEO show that USR could complement the voxelization feature to comprehensively characterize residue structure information and significantly improve the model assessment accuracy. DeepUMQA outperformed the state-of-the-art single-model quality assessment methods, including ProQ2, ProQ3, ProQ3D, Ornate, VoroMQA, and DeepAccNet. AvailabilityThe source code and executable are freely available at https://github.com/iobio-zjut/DeepUMQA. Contactzgj@zjut.edu.cn

bioinformatics↗

bioRxiv2021

m6A modifications regulate intestinal immunity and rotavirus infection

N6-methyladenosine (m6A) is an abundant mRNA modification and affects many biological processes. However, how m6A levels are regulated during physiological or pathological processes such as virus infections, and the in vivo function of m6A in the intestinal immune defense against virus infections are largely unknown. Here, we uncover a novel antiviral function of m6A modification during rotavirus (RV) infection in small bowel intestinal epithelial cells (IECs). We found that rotavirus infection induced global m6A modifications on mRNA transcripts by down-regulating the m6a eraser ALKBH5. Mice lacking the m6A writer enzymes METTL3 in IECs (Mettl3{Delta}IEC) were resistant to RV infection and showed increased expression of interferons (IFNs) and IFN-stimulated genes (ISGs). Using RNA-sequencing and m6A RNA immuno-precipitation (RIP)-sequencing, we identified IRF7, a master regulator of IFN responses, as one of the primary m6A targets during virus infection. In the absence of METTL3, IECs showed increased Irf7 mRNA stability and enhanced type I and III IFN expression. Deficiency in IRF7 attenuated the elevated expression of IFNs and ISGs and restored susceptibility to RV infection in Mettl3{Delta}IEC mice. Moreover, the global m6A modification on mRNA transcripts declined with age in mice, with a significant drop from 2 weeks to 3 weeks post birth, which likely has broad implications for the development of intestinal immune system against enteric viruses early in life. Collectively, we demonstrated a novel host m6A-IRF7-IFN antiviral signaling cascade that restricts rotavirus infection in vivo.

immunology↗

bioRxiv2021

Mutationathon: towards standardization in estimates of pedigree-based germline mutation rates

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various non-human species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and how to appropriately account for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a "Mutationathon", a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a two-fold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.

evolutionary biology↗

bioRxiv2021

The Lambda variant of SARS-CoV-2 has a better chance than the Delta variant to escape vaccines

The newly emerging variants of SARS-CoV-2 from India (Delta variant) and South America (Lambda variant) have led to a higher infection rate of either vaccinated or unvaccinated people. We found that sera from Pfizer-BioNTech vaccine remain high reactivity toward the receptor binding domain (RBD) of Delta variant while it drops dramatically toward that of Lambda variant. Interestingly, the overall titer of antibodies of Pfizer-BioNTech vaccinated individuals drops 3-fold after 6 months, which could be one of major reasons for breakthrough infections, emphasizing the importance of potential third boost shot. While a therapeutic antibody, Bamlanivimab, decreases binding affinity to Delta variant by ~20 fold, it fully lost binding to Lambda variant. Structural modeling of complexes of RBD with human receptor, Angiotensin Converting Enzyme 2 (ACE2), and Bamlanivimab suggest the potential basis of the change of binding. The data suggest possible danger and a potential surge of Lambda variant in near future.

immunology↗

bioRxiv2021

Modeling bottlenecks, modularity, and context-dependency in behavioral control

In almost all animals, the transfer of information from the brain to the motor circuitry is facilitated by a relatively small number of neurons, leading to a constraint on the amount of information that can be transmitted. Our knowledge of how animals encode information through this pathway, and the consequences of this encoding, however, is limited. In this study, we use a simple feed-forward neural network to investigate the consequences of having such a bottleneck and identify aspects of the network architecture that enable robust information transfer. We are able to explain some recently observed properties of descending neurons - that they exhibit a modular pattern of connectivity and that their excitation leads to consistent alterations in behavior that are often dependent upon the prior behavioral state (context-dependency). Our model predicts that in the presence of an information bottleneck, such a modular structure is needed to increase the efficiency of the network and to make it more robust to perturbations. However, it does so at the cost of an increase in context-dependency. Despite its simplicity, our model is able to provide intuition for the trade-offs faced by the nervous system in the presence of an information processing constraint and makes predictions for future experiments.

animal behavior and cognition↗

bioRxiv2021

Artificial Neural Networks for classification of single cell gene expression

BackgroundSingle-cell transcriptome (SCT) sequencing technology has reached the level of high-throughput technology where gene expression can be measured concurrently from large numbers of cells. The results of gene expression studies are highly reproducible when strict protocols and standard operating procedures (SOP) are followed. However, differences in sample processing conditions result in significant changes in gene expression profiles making direct comparison of different studies difficult. Unsupervised machine learning (ML) uses clustering algorithms combined with semi-automated cell labeling and manual annotation of individual cells. They do not scale up well and a workflow used on a specific dataset will not perform well with other studies. Supervised ML classification shows superior classification accuracy and generalization properties as compared to unsupervised ML methods. We describe a supervised ML method that deploys artificial neural networks (ANN), for 5-class classification of healthy peripheral blood mononuclear cells (PBMC) from multiple diverse studies. ResultsWe used 58 data sets to train ANN incrementally - over ten cycles of training and testing. The sample processing involved four protocols: separation of PBMC, separation of PBMC + enrichment (by negative selection), separation of PBMC + FACS, and separation of PBMC + MACS. The training data set included between 85 and 110 thousand cells, and the test set had approximately 13 thousand cells. Training and testing were done with various combinations of data sets from four principal data sources. The overall accuracy of classification on independent data sets reached 5-class classification accuracy of 94%. Classification accuracy for B cells, monocytes, and T cells exceeded 95%. Classification accuracy of natural killer (NK) cells was 75% because of the similarity between NK cells and T cell subsets. The accuracy of dendritic cells (DC) was low due to very low numbers of DC in the training sets. ConclusionsThe incremental learning ANN model can accurately classify the main types of PBMC. With the inclusion of more DC and resolving ambiguities between T cell and NK cell gene expression profiles, we will enable high accuracy supervised ML classification of PBMC. We assembled a reference data set for healthy PBMC and demonstrated a proof-of-concept for supervised ANN method in classification of previously unseen SCT data. The classification shows high accuracy, that is consistent across different studies and sample processing methods.

bioinformatics↗

bioRxiv2021

Molecular Pathophysiology of Cardiac Injury and Cardiac Microthrombi in Fatal COVID-19: Insights from Clinico-histopathologic and Single Nuclei RNA Sequencing Analyses

Cardiac injury is associated with critical COVID-19, yet its etiology remains debated. To elucidate the pathogenic mechanisms of COVID-19-associated cardiac injury, we conducted a single-center prospective cohort study of 69 COVID-19 decedents. Of six cardiac histopathologic features, microthrombi was the most commonly detected (n=48, 70%). We tested associations of cardiac microthrombi with biomarkers of inflammation, cardiac injury, and fibrinolysis and with in-hospital antiplatelet therapy, therapeutic anticoagulation, and corticosteroid treatment, while adjusting for multiple clinical factors, including COVID-19 therapies. Higher peak ESR and CRP during hospitalization were independently associated with higher odds of microthrombi. Using single nuclei RNA-sequence analysis, we discovered an enrichment of pro-thrombotic/anti-fibrinolytic, extracellular matrix remodeling, and immune-potentiating signaling amongst cardiac fibroblasts in microthrombi-positive COVID-19 hearts relative to microthrombi-negative COVID-19. Non-COVID-19 non-failing hearts were used as reference controls. Our cumulative findings identify the specific transcriptomic changes in cardiac fibroblasts as salient features of COVID-19-associated cardiac microthrombi.

pathology↗

bioRxiv2021

Dual-lipid metabolomics revealed the communication of MTB or MB with Bovine alveolar macrophages in lipid metabolisms

M. tuberculosis(MTB) and M. bovis(MB) of the Mycobacterium tuberculosis complex (MTBC) are the causative agents of the notorious infectious disease tuberculosis(TB) in a range of mammals, including cattle and human. The lipid composition of MTB/MB performed imperative function as invading host macrophage. In the present study, a dual-lipid metabolomics were used to elucidate the differences in lipid composition of MTB and MB and the different responses in lipid metabolisms of bovine alveolar macrophage challenged by MTB/MB. The lipid metabolomics of MTB and MB indicated that there were significant differences in lipid composition of both bacteria that the level of various lipids belonged to Glycerophospholipids, Sterol Lipids, Fatty Acyls and Polyketides exhibited differences between MTB and MB. Meanwhile, both MTB and MB with different lipid composition could invoked different responses in lipid metabolisms of the host macrophage. MTB infection mainly induced the increase in content of Polyketides and Glycerophospholipids in macrophages, whereas MB infection induced the level of Glycerophospholipids and Sterol Lipids of macrophages. Furthermore, we identified TAG 13:0-18:5-18:5 of MTB and PC(16:1(9E)/0:0), PI(20:2(11Z,14Z)/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), 4,6-Decadiyn-1-ol isovalerate and LacCer(d18:1/24:1(15Z)) of MB caused the different variations in lipid metabolisms of macrophage following MTB/MB attacks, respectively. Finally, we proposed MTB and MB with different lipid compositions could successfully colonize in macrophage by different mechanisms that MTB could promote the formation of foam cells of macrophage for its colonization and development, while MB mainly through suppressing the macrophage autophagy to escape the immune responses of host. ImportanceThe differences in lipid composition of MTB and MB and the different responses in lipid metabolisms of bovine alveolar macrophage challenged by MTB/MB were elucidated in this study. The lipid composition of MTB and MB exhibited significantly different patterns, which could induced different responses of the host macrophage during the infection process of MTB or MB, respectively. MTB infection mainly induced the increase in content of Polyketides and Glycerophospholipids in macrophages, whereas MB infection induced the level of Glycerophospholipids and Sterol Lipids of macrophages.The results presented here thus provides a comprehensively dual-lipid metabolomics profile in MTB/MB and MTB/MB-attacked macrophages, which deepened our understanding of the interaction between host and pathogens in lipid metabolisms.

microbiology↗

bioRxiv2021

Tissue-specific modification of cellular bioelectrical activities using the chemogenetic tool, DREADD, in zebrafish

Cellular electronic activity plays an essential role in neuronal communication. Manipulation and visualization of cellular membrane potential remain essential tasks in order to study electrical signaling in living organisms. Light-controlled optogenetic and designed chemical-controlled chemogenetic tools were developed to manipulate cellular electric activities for neuroscience research. One of the most common chemogenetic tools is DREADD (designer receptors exclusively activated by designer drugs). It has been extensively utilized due to its convenience and long-lasting effects in murine and primate models, but not in zebrafish, a leading model organism in various research fields. Here, we first establish multiple tissue-specific transgenic zebrafish lines that express two different DREADDs with a genetically encoded voltage indicator, ASAP2s. We observed voltage changes in zebrafish melanophores, epidermis, and neurons by hM4DGi or rM3DGs receptors measured by ASAP2s fluorescence intensity. Alteration to melanophore bioelectricity by DREADD generated dynamic electric signals and resulted in morphological alterations to pigment cells. We also tested a few agonists and found that the latest generation performs better than clozapine N-oxide (CNO). Collectively, our experiments demonstrate that DREADD can be utilized to manipulate cell-specific membrane potential in the zebrafish model. The availability of this tool in zebrafish will offer a new resource for a variety of bioelectricity research fields such as neuroscience, cardiology, and developmental biology.

developmental biology↗

bioRxiv2021

Comparative proteome analysis revealed the differences in responses of bovine alveolar macrophages to both M.tb and Mb infection

Bovine tuberculosis, caused by both MTB(Mycobacterium tuberculosis) and MB(Mycobacterium bovis), is one of the most serious zoonotic diseases in the world. Both pathogenic MTB and MB interact closely with the host alveolar macrophages. However, the mechanisms of defense response of macrophages to MTB or MB still need further researches. Presently, in-depth comparative proteome analysis was performed on the MB- and MTB- infected macrophage. We identified that macrophages was more sensitive to the MB infection. Both pathogens could induce strong energy metabolism of macrophages. To eliminate MB and protect the host, a bunch of proteins and signaling which involved in autophagy- and inflammatory-related progresses were highly activated in macrophages following MB infection. In contrast, only proteins relevant to energy metabolisms were highly expressed in macrophages following MTB infection. In summary, we proposed that macrophages were more sensitive to MB attacks and could deployed proteins functioned in autophagy- and inflammatory-related progresses to protect the host. Our research provide a novel insight into the different mechanisms of defense responses of macrophages to both MTB and MB infection.

bioinformatics↗

bioRxiv2021

Detection of pigeon circoviruses in ticks of sheep and camels in Inner Mongolia, China

Circovirus is one of the smallest known DNA viruses infecting animals. In this report, circovirus was detected in two tick species- Hyalomma asiaticum and Dermacentor nuttalli collected from sheep and camels in Inner Mongolia, China by high-throughput sequencing. The reverse semi-nested PCR assay revealed a complete genomic sequence of 2042 base pairs of cyclic single-stranded DNA (ssDNA). Evolutionary analysis further revealed that it belonged to circovirus with two major open read frames (ORFs) that putatively encode replicase and capsid proteins, respectively. Sequence and phylogenetic analysis suggested that the circovirus belonged to pigeon circovirus. The results demonstrated the presence of pigeon circovirus in ticks in Inner Mongolia, which provide the basis for future exploration of the prevalence of pigeon circovirus in Inner Mongolia and the pathogens carried by ticks in Inner Mongolia.

microbiology↗

bioRxiv2021

Phylogenetic Analysis of Crimean-Congo Hemorrhagic Fever Virus in Inner Mongolia, China

Crimean-Congo hemorrhagic fever virus (CCHFV) is a tick-borne arbovirus that can cause bleeding and death in humans. The mortality rate in humans is between 5 to 30%. The pathogen is prevalent in more than 30 countries in the world. In China, reports of strains of CCHFV have been concentrated in Xinjiang province. However, the CCHFV strain has never been reported in Inner Mongolia, China. This study reports new CCHFV strains, HANM-18, from Hyalomma asiaticum and Hyalomma dromedarii collected in Alxa Left Banner and Alxa Right Banner in Inner Mongolia. Complete sequences of CCHFV were obtained by the nested PCR technique and used for analyzing the identity and evolutionary relationship with other CCHFV strains. Interestingly, our results showed that the S and L fragments of the HANM-18 strain had high degrees of identity with Xingjiang isolate strains, and the M fragment had significant identity with South African isolates. These analyses also indicate that the HANM-18 strain may have been prevalent in northwest Inner Mongolia for many years. This discovery will be helpful in CCHF prevention and control in Inner Mongolia, and it also adds new evidence to the epidemiology of CCHF in China.

microbiology↗

bioRxiv2021

Revision of the genus Dichaetophora Duda (Diptera: Drosophilidae), part I: DNA bar-coding and molecular phylogenetic reconstruction

The genus Dichaetophora is currently comprised of 67 formally described species assigned into five species groups, i.e., agbo, tenuicauda, acutissima, sinensis and trilobita. In the present study, we challenged to delimit species from a huge amount of samples of Dichaetophora and allied taxa (the genus Mulgravea and the subgenus Dudaica of Drosophila) collected from a wide range of the Oriental and east Palearctic regions. We first sorted all specimens into morpho-species, which were tentatively classified into the species groups of Dichaetophora, Mulgravea and Dudaica based on the morphological diagnoses for these supraspecific taxa. Then, we selected representative specimen(s) for each morpho-species and subjected them to barcoding of COI (the cytochrome c oxidase subunit I gene) sequences. The applied ABGD (automatic barcode gap discovery) algorithm estimated a total of 222 MOTUs (molecular operational taxonomic units). Although most of the morpho-species were recognized as individual MOTUs, some others were divided into multiple MOTUs or combined into a single MOTU, suggesting the existence of cryptic sibling species, subspecies or intraspecific genetic varieties. Out of the 222 MOTUs, 88 representing the supraspecific taxa of Dichaetophora, Mulgravea and Dudaica were selected, along with 33 species from major genera and subgenera of Drosophila in the tribe Drosophilini, as in-group (four species from the tribe Colocasiomyini as out-group) for phylogenetic reconstruction. We analyzed a dataset of concatenated nucleotide sequences of 12 nuclear gene markers by the maximum likelihood and Bayesian inference methods. As a result, the three focal taxa (i.e., Dichaetophora, Mulgravea and Dudaica) formed a clade, which we called the "pan-Dichaetophora". Within this large clade, the agbo, tenuicauda, sinensis and trilobita groups of Dichaetophora, Mulgravea and Dudaica were recovered as monophyletic groups, but Dichaetophora and its acutissima group were regarded as paraphyletic. In addition, two clusters were recognized among ungrouped MOTUs of Dichaetophora. Thus, the present study has uncovered some problems in the taxonomy of the pan-Dichaetophora. Solving such problems will be challenged in Part II of this serial work.

zoology↗

bioRxiv2021

Neuron-radial glial cell communication via BMP/Id1 signaling maintains the regenerative capacity of the adult zebrafish telencephalon

The mechanisms of the management of the neural stem cell (NSC) pool underlying the regenerative capacity of the adult zebrafish brain are not understood. We show that Bone Morphogenetic Proteins (BMPs) which are exclusively expressed by neurons in the adult telencephalon and the helix-loop-helix (HLH) transcription co-regulator, Inhibitor of differentiation 1 (Id1), control quiescence of NSCs. Upon injury, lack of id1 function leads to an initial over-proliferation and subsequent loss of NSCs and the regenerative capacity. BMP/Id1 signaling up-regulates the transcription factor her4.1 which is also a target of Notch signaling mediating short-range control of NSC quiescence. Hence, the two signaling systems converge onto Her4.1. Our data show that neurons feedback on NSC proliferation. BMP1/Id1 signaling appears as the predominant safeguard of the NSC pool under regenerative conditions while Notch signaling is sufficient to maintain NSCs under homeostatic baseline neurogenesis in the uninjured animal.

developmental biology↗

bioRxiv2021

Distance-guided protein folding based on generalized descent direction

Advances in the prediction of the inter-residue distance for a protein sequence have increased the accuracy to predict the correct folds of proteins with distance information. Here, we propose a distance-guided protein folding algorithm based on generalized descent direction, named GDDfold, which achieves effective structural perturbation and potential minimization in two stages. In the global stage, random-based direction is designed using evolutionary knowledge, which guides conformation population to cross potential barriers and explore conformational space rapidly in a large range. In the local stage, locally rugged potential landscape can be explored with the aid of conjugate-based direction integrated into a specific search strategy, which can improve exploitation ability. GDDfold is tested on 347 proteins of a benchmark set, 24 FM targets of CASP13 and 20 FM targets of CASP14. Results show that GDDfold correctly folds (TM-score [≥] 0.5) 316 out of 347 proteins, where 65 proteins have TM-scores that are greater than 0.8, and significantly outperforms Rosetta-dist (distance-assisted fragment assembly method) and L-BFGSfold (distance geometry optimization method). On CASP FM targets, GDDfold is comparable with five state-of-the-art methods, namely, Quark, RaptorX, Rosetta, MULTICOM and trRosetta in the CASP 13 and 14 server groups.

bioinformatics↗