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Biology subjects

Jiang, H.

Publications and source records attributed to Jiang, H..

At least 199 records · Page 11Linked to original sources

De novo design of buttressed loops for sculpting protein functions

In natural proteins, structured loops play central roles in molecular recognition, signal transduction and enzyme catalysis. However, because of the intrinsic flexibility and irregularity of loop regions, organizing multiple structured loops at protein functional sites has been very difficult to achieve by de novo protein design. Here we describe a solution to this problem that generates structured loops buttressed by extensive hydrogen bonding interactions with two neighboring loops and with secondary structure elements. We use this approach to design tandem repeat proteins with buttressed loops ranging from 9 to 14 residues in length. Experimental characterization shows the designs are folded and monodisperse, highly soluble, and thermally stable. Crystal structures are in close agreement with the computational design models, with the loops structured and buttressed by their neighbors as designed. We demonstrate the functionality afforded by loop buttressing by designing and characterizing binders for extended peptides in which the loops form one side of an extended binding pocket. The ability to design multiple structured loops should contribute quite generally to efforts to design new protein functions.

biochemistry↗

Systematic characterization of site-specific proline hydroxylation using hydrophilic interaction chromatography and mass spectrometry

We have developed a robust workflow for the identification of proline hydroxylation sites in proteins, using a combination of hydrophilic interaction chromatography (HILIC) enrichment and high-resolution nano-Liquid Chromatography-Mass Spectrometry (LC-MS) together with refining and filtering parameters during data analysis. Using this approach, we have combined data from cell lines treated with either the prolyl hydroxylase (PHD) inhibitor, Roxadustat (FG-4592), or with the proteasome inhibitor MG-132, or with a DMSO control, to identify a total of 4,993 and 3,247 proline hydroxylation sites, respectively, in HEK293 and RCC4 cells. A subset of 1,954 (HEK293) and 1,253 (RCC4) non-collagen proline hydroxylation sites with high confidence were inhibited by FG-4592 treatment. Features characteristic of proline hydroxylated peptides were identified, which were consistent between the HEK293 and RCC4 datasets. The more hydrophilic HILIC fractions were enriched in peptides containing hydroxylated proline residues, which showed characteristic differences in charge and mass distribution, as compared with either unmodified, or oxidised peptides. Furthermore, we discovered that the intensity of the diagnostic hydroxyproline immonium ion was dependent upon parameters including the MS collision energy setting, parent peptide concentration and the sequence of amino acids adjacent to the modified proline. We show using synthetic peptides that a combination of retention time in LC and optimised MS parameter settings allows reliable identification of proline hydroxylation sites in peptides, even when multiple prolines residues are present. Focussing on proteins in which newly identified proline hydroxylation sites were inhibited by the pan-PHD inhibitor, FG-4592, showed enrichment for proteins involved in metabolism of RNA, mRNA splicing and cell cycle regulation, including the protein phosphatase 1 regulatory subunit, Repo-Man (CDCA2). We show that Repo-Man is hydroxylated at P604 and in the accompanying study by Druker et al. 1, we present a combination of cellular and biochemical evidence that hydroxylation of Repo-Man at P604 is important for its function in controlling mitotic progression.

biochemistry↗

Functional analysis of Cdc20 reveals a critical role of CRY box in mitotic checkpoint signaling

Accurate chromosome segregation is coordinated by the spindle assembly checkpoint (SAC) through its effector the mitotic checkpoint complex (MCC), to inhibit the anaphase-promoting complex or cyclosome (APC/C). Cdc20 is an essential mitotic regulator since it promotes mitotic exit through activating the APC/C and monitors kinetochore-microtubule attachment through activating the SAC. The proper functioning of Cdc20 requires multiple interactions with APC/C and MCC subunits. To functionally assess each of these interactions within cells requires efficient depletion of endogenous Cdc20, which is highly difficult to achieve by RNAi. Here we generated Cdc20 RNAi sensitive cell lines by CRISPR/Cas9 which display a penetrant metaphase arrest phenotype by a single RNAi treatment. In this null background, we accurately measured the contribution of each known motif of Cdc20 on APC/C and SAC activation. The CRY box, a previously identified degron was found to be critical for the SAC by promoting the MCC formation and stabilizing the interaction between the MCC and APC/C. These data reveal additional regulatory components within the SAC and establish a novel method to interrogate Cdc20 function.

cell biology↗

Chimeric oncolytic adenovirus evades neutralizing antibodies from human patients and exhibits enhanced anti-glioma efficacy in immunized mice

BACKGROUNDOncolytic adenoviruses, such as Delta-24-RGD, show promise as a potential breakthrough in treating patients with high-grade gliomas. However, their effectiveness against gliomas can be hindered by the presence of neutralizing antibodies. METHODSProduction of human neutralizing antibodies against adenoviruses was assessed in two cohorts of patients with malignant gliomas treated with Delta-24-RGD in a phase 1 clinical trial. Sera containing neutralizing antibodies were also obtained from mice immunized with intramuscular injections of wild-type Ad5. Chimeric adenovirus was constructed using molecular cloning, and its activity was assessed in vitro using quantitative PCR, western blot, and transmission electron microscopy. The therapeutic efficacy of the chimeric virus was tested in vivo using sera from patients previously treated with Delta-24-RGD and immunocompetent murine models of glioma. RESULTSExamination of sera from patients with malignant gliomas treated with Delta-24-RGD revealed that in the cohort treated with multiple injections of this oncolytic adenovirus, a higher percentage of patients developed neutralizing antibodies when compared to the patients treated with a single injection of Delta-24-RGD. Of note, long-term survival was only observed in patients who received a single injection. Delta-24-RGD-H43m, a chimeric oncolytic adenovirus engineered to overcome virus neutralization, demonstrated a potent anti-glioma effect both in vitro and in vivo. This chimeric virus showed resilience against anti-Ad5 neutralizing antibodies and conferred better therapeutic efficacy compared to Delta-24-RGD in mice with immunity against Ad5. Of further clinical relevance, Delta-24-RGD-H43m also evaded the inhibitory effects of sera from human patients treated with Delta-24-RGD. CONCLUSIONSThe development of neutralizing antibodies due to multiple virus injections was associated with lower frequency of long-term survivors in a clinical trial. The new chimeric virus shows increased resilience to inactivation by the sera of human patients compared to the parental virus. These findings lay the foundation for a novel oncolytic virus treatment approach targeting a significant percentage of glioma patients with prior exposure to adenovirus.

cancer biology↗

ATUM-Tomo: A multi-scale approach to cellular ultrastructure by combined volume scanning electron microscopy and electron tomography

Like other volume electron microscopy approaches, Automated Tape Collecting Ultramicrotomy (ATUM) enables imaging of serial sections deposited on thick plastic tapes by scanning electron microscopy (SEM). ATUM is unique in enabling hierarchical imaging and thus efficient screening for target structures, as needed for correlative light and electron microscopy. However, SEM of sections on tape can only access the section surface, thereby limiting the axial resolution to the typical size of cellular vesicles with an order of magnitude lower than the acquired xy resolution. In contrast, serial-section electron tomography (ET), a transmission electron microscopy-based approach, yields isotropic voxels at full EM resolution, but requires deposition of sections on electron-stable thin and fragile films, thus making screening of large section libraries difficult and prone to section loss. To combine the strength of both approaches, we developed ATUM-Tomo, a hybrid method, where sections are first reversibly attached to plastic tape via a dissolvable coating, and after screening detached and transferred to the ET-compatible thin films. ATUM-SEM of serial semi-thick sections and consecutive ET of selected re-mounted sections combines SEMs fast target recognition and coarse rendering capability with high-resolution volume visualizations, respectively, thus enabling multi-scale interrogation of cellular ultrastructure. As a proof-of-principle, we applied correlative ATUM-Tomo to study ultrastructural features of blood brain barrier (BBB) leakiness around microthrombi in a mouse model of traumatic brain injury. Microthrombi and associated sites of BBB leakiness were identified by confocal imaging of injected fluorescent and electron-dense nanoparticles, then relocalized by ATUM-SEM, and finally interrogated by correlative ATUM-Tomo. This workflow is a seamless zoom-in on structural BBB pathology from the micro- to the nanometer scale. Overall, our new ATUM-Tomo approach will substantially advance ultrastructural analysis of biological phenomena that require cell- and tissue-level contextualization of the finest subcellular textures.

neuroscience↗

EMDiffuse: a diffusion-based deep learning method augmenting ultrastructural imaging and volume electron microscopy

Electron microscopy (EM) revolutionized the way to visualize cellular ultrastructure. Volume EM (vEM) has further broadened its three-dimensional nanoscale imaging capacity. However, intrinsic trade-offs between imaging speed and quality of EM restrict the attainable imaging area and volume. Isotropic imaging with vEM for large biological volumes remains unachievable. Here we developed EMDiffuse, a suite of algorithms designed to enhance EM and vEM capabilities, leveraging the cutting-edge image generation diffusion model. EMDiffuse demonstrates outstanding denoising and super-resolution performance, generates realistic predictions without unwarranted smoothness, improves predictions resolution by [~]30%, and exhibits excellent transferability by taking only one pair of images to fine-tune. EMDiffuse also pioneers the isotropic vEM reconstruction task, generating isotropic volume similar to that obtained using advanced FIB-SEM even in the absence of isotropic training data. We demonstrated the robustness of EMDiffuse by generating isotropic volumes from six public datasets obtained from different vEM techniques and instruments. The generated isotropic volume enables accurate organelle reconstruction, making 3D nanoscale ultrastructure analysis faster and more accessible and extending such capability to larger volumes. More importantly, EMDiffuse features self-assessment functionalities and guarantees reliable predictions for all tasks. We envision EMDiffuse to pave the way for more in-depth investigations into the intricate subcellular nanoscale structures within large areas and volumes of biological systems.

cell biology↗

Sustained hippocampal theta-oscillations reflect experience-dependent learning in bidirectional temporal-order memory retrieval

Navigating within our neighborhood, learning a set of concepts, or memorizing a story, requires remembering the relationship between individual items that are presented sequentially. Theta activity in the mammalian hippocampus has been related to the encoding and recall of relational structures embedding episodic memories. However, how theta oscillations are involved in retrieving temporal order information in opposing directionality (forward vs backward) has not been characterized. Here, using intracranial recordings from 10 human epileptic patients of both genders with hippocampal electrodes, we tested the patients with a temporal order memory task in which they learned the spatial relationship among individual items arranged along a circular track and were tested on both forward-cued and backward-cued retrieval conditions. We found that sustained high-power oscillatory events in the hippocampal theta (2-8 Hz) band, as quantified by Pepisode rate, were higher for the backward conditions during the later stage but not in the earlier stage. The theta Pepisode results are consistent with the behavioral memory performance. In contrast, we observed a stronger effect of forward than backward retrieval for the gamma (30-70 Hz) Pepisode rate irrespective of stages. Our results revealed differential roles of theta vs. gamma oscillations in the retrieval of temporal order and how theta oscillations are specifically implicated in the learning process for efficient retrieval of temporal order memories under opposing directionality. Significance statementWhile the hippocampus is critical to link events into unitary episodes, the effect of repeated experiences, or learning, on these processes is not entirely clear. We discovered that hippocampal theta oscillation in humans is modulated by repeated experiences, which in turn increases the efficacy of backward-cued memory retrieval of temporal order. This study revealed an important physiological signature characterizing the role of experiences and learning in bidirectional temporal memory retrieval. Journal sectionBehavioral/Cognitive

neuroscience↗

Aster-dependent non-vesicular transport facilitates dietary cholesterol uptake

Intestinal cholesterol absorption is an important contributor to systemic cholesterol homeostasis. Niemann-Pick C1 Like 1 (NPC1L1), the target of the drug ezetimibe (EZ), assists in the initial step of dietary cholesterol uptake. However, how cholesterol moves downstream of NPC1L1 is unknown. Here we show that Aster-B and Aster-C are critical for non-vesicular cholesterol movement in enterocytes, bridging NPC1L1 at the plasma membrane (PM) and ACAT2 in the endoplasmic reticulum (ER). Loss of NPC1L1 diminishes accessible PM cholesterol in enterocytes and abolishes Aster recruitment to the intestinal brush border. Enterocytes lacking Asters accumulate cholesterol at the PM and display evidence of ER cholesterol depletion, including decreased cholesterol ester stores and activation of the SREBP-2 transcriptional pathway. Aster-deficient mice have impaired cholesterol absorption and are protected against diet-induced hypercholesterolemia. Finally, we show that the Aster pathway can be targeted with a small molecule inhibitor to manipulate dietary cholesterol uptake. These findings identify the Aster pathway as a physiologically important and pharmacologically tractable node in dietary lipid absorption. One-Sentence SummaryIdentification of a targetable pathway for regulation of dietary cholesterol absorption

physiology↗

KISS1 is a potential immunological and prognostic biomarker for cancer metastasis in pan-cancer and affects breast cancer in a different way

Metastasis to other organs accounts for the majority of death in cancer patients. Metastatic capacity enables tumor cells resist to chemotherapy. KISS1 had been found to suppress metastasis in cancers like melanoma, but improve the metastatic phenotype of breast cancers, which means its role in tumor metastasis is tissue context-dependent. This character suggests the KISS1 might have promising potential to interpret tumor metastasis in a pan-cancer perspective. Here, we analyzed the potential functions of KISS1 in pan-cancer, especially in breast cancer, by the datasets of TCGA and GTEx. KISS1 exhibited a different expression status between mRNA level and protein level in pan-cancers, with a significant association between KISS1 expression and prognosis of cancer patients. Besides, the correlation between KISS1 expression and immune cell infiltration, immunosuppressive cells, immune checkpoint genes, TMB, MSI, tumor purity and HRD indicates the potential role in regulating immunotherapy. Thereafter, we further clarified the role of KISS1 in promoting metastasis in breast cancer. Furthermore, we found that the post-translational modification may explains the KISS1 protein stability in breast cancers. In summary, our first pan-cancer study offers new insights and relatively comprehensive understandings of the oncogenic roles of KISS1 across various cancers.

genetics↗

Entropy-based decoy generation methods for accurate FDR estimation in large-scale metabolomics annotations.

Large-scale metabolomics research faces challenges in accurate metabolite annotation and false discovery rate (FDR) estimation. Recent progress in addressing these challenges has leveraged experience from proteomics and inspiration from other sciences. Although the target-decoy strategy has been applied to metabolomics, generating reliable decoy libraries is difficult due to the complexity of metabolites. Additionally, continuous bioinformatic efforts are necessary to increase the utilization of growing spectra resources while reducing false identifications. Here we introduce the concept of ion entropy and present two entropy-based decoy generation methods. The assessment of public spectral databases using ion entropy validated it as a good metric for ion information content in massive metabolomics data. The decoy generation method developed based on this concept outperformed current representative decoy strategies in metabolomics and achieved the best FDR estimation performance. We analyzed 47 public metabolomics datasets using the constructed workflow to provide instructive suggestions. Finally, we present MetaPhoenix, a tool equipped with a well-constructed FDR estimation workflow that facilitates the development of accurate FDR-controlled analysis in the metabolomics field.

bioinformatics↗

Comprehensive Assessment of Eleven de novo HiFi Assemblers on Complex Eukaryotic Genomes and Metagenomes

BackgroundPacific Bioscience HiFi sequencing technology generates long reads (>10 kbp) with very high accuracy (less than 0.01% sequencing error). While several de novo assembly tools are available for HiFi reads, there are no comprehensive studies on the evaluation of these assemblers. ResultsWe evaluated the performance of eleven de novo HiFi assemblers on (i) real data for three eukaryotic genomes, (ii) 34 synthetic datasets with different ploidy, sequencing coverage levels, heterozygosity rates and sequencing error rates, (iii) one real metagenomic dataset, and (iv) five synthetic metagenomic datasets with different composition abundance and heterozygosity rates. The nine assemblers were evaluated using QUAST (Quality Assessment Tool) and BUSCO (Benchmarking Universal Single-Copy Ortholog). We also used several additional criteria, namely, completion rate, single-copy completion rate, duplicated completion rate, average proportion of largest category, average distance difference, quality value, run-time and memory utilization. On complex eukaryotic genomes, Hifiasm had a clear advantage over the other assemblers in all tested experiments. On synthetic datasets, Hifiasm, HiCanu, and HiFlye performed equally well. Shasta and Peregrine had good performance across varying ploidy, but required high computational resources. On metagenomic datasets, Hifiasm-meta demonstrated a clear advantage over other assemblers. ConclusionWe carried out a comprehensive benchmarking study of commonly used assemblers on complex eukaryotic genomes and metagenomes. Our study will help the research community to choose the most appropriate assembler for their data and identify possible improvements in assembly algorithms.

genomics↗

Identification and Characterization of CtUGT3 as the Key Player of Astragalin Biosynthesis in Safflower

Safflower (Carthamus tinctorius L.) flowers are used as a traditional Chinese medicine for a long history. Flavonoids are the main bioactive components in safflower flowers, and most of them exist in the form of flavonoid glycosides. Only few glycosyltransferases have been identified in safflower. To reveal the uridine diphosphate glycosyltransferase (UGT) involved in flavonoid glycosides biosynthesis in safflower, a metabolomics and transcriptome analysis was performed by using the flowers under different light qualities treatments. Three differentially expressed UGT genes were screened, and their expressions were significantly related with concentrations of 9 flavonoid O-glycosides. Safflower corolla protoplasts were further used to confirm flavonoid O-glycosylation ability of UGT candidates. The astragalin (kaempferol 3-O-glucoside) content was only significantly increased when CtUGT3 was overexpressed in protoplasts. The biochemical properties and kinetic parameters of CtUGT3 were determined. CtUGT3 also showed flavonoid 3-OH and 7-OH glycosylation activities in vitro. Molecular modeling and site-directed mutagenesis revealed that E384 and S276 were critical catalytic residues for the 3-OH glycosylation of CtUGT3. These results demonstrate that CtUGT3 has a flavonoid 3-OH glycosylation function and is involved in the biosynthesis of astragalin in safflower. This study provides insights into the catalytic mechanisms of flavonoid O-glycosyltransferases, and makes a reference for flavonoid biosynthesis genes research in medicinal plants.

plant biology↗

Comprehensive computational analysis of the SRK-SP11 molecular interaction underlying self-incompatibility in Brassicaceae using improved structure prediction for cysteine-rich proteins

Plants employ self-incompatibility (SI) to promote cross-fertilization. In Brassicaceae, this process is regulated by the formation of a complex between the pistil determinant S receptor kinase (SRK) and the pollen determinant S-locus protein 11 (SP11, also known as S-locus cysteine-rich protein, SCR). In our previous study, we used the crystal structures of two eSRK-SP11 complexes in Brassica rapa S8 and S9 haplotypes and nine computationally predicted complex models to demonstrate that only the SRK ectodomain (eSRK) and SP11 pairs derived from the same S haplotype exhibit high binding free energy. However, predicting the eSRK-SP11 complex structures for the other 100+ S haplotypes and genera remains difficult because of SP11 polymorphism in sequence and structure. Although protein structure prediction using AlphaFold2 exhibits considerably high accuracy for most protein monomers and complexes, 46% of the predicted SP11 structures that we tested showed < 75 mean per-residue confidence score (pLDDT). Here, we demonstrate that the use of curated multiple sequence alignment (MSA) for cysteine-rich proteins significantly improved model accuracy for SP11 and eSRK-SP11 complexes. Additionally, we calculated the binding free energies of the predicted eSRK-SP11 complexes using molecular dynamics (MD) simulations and observed that some Arabidopsis haplotypes formed a binding mode that was critically different from that of B. rapa S8 and S9. Thus, our computational results provide insights into the haplotype-specific eSRK-SP11 binding modes in Brassicaceae at the residue level. The predicted models are freely available at Zenodo, https://doi.org/10.5281/zenodo.8047768.

bioinformatics↗

Screening for variable drug responses using human iPSC cohorts

We have developed a laboratory-based drug screening platform that uses a cohort of human induced pluripotent stem cell (hiPSC) lines, derived from different donors, to predict variable drug responses of potential clinical relevance. This builds on recent findings that pluripotent hiPSC lines express a broad repertoire of gene transcripts and proteins, whose expression levels reflect the genetic identity of the donor. We demonstrate that a cohort of hiPSC lines from different donors can be screened efficiently in their pluripotent state, using high-throughput Cell Painting assays. Variable phenotypic responses between hiPSC lines were detected with a wide range of clinically approved drugs, in use across multiple disease areas. Furthermore, information on mechanisms of drug-cell interactions underlying the observed variable responses was derived by using quantitative proteomic analysis to compare sets of hiPSC lines that had been stratified objectively, based upon variable response, Cell Painting data. We propose that information derived from comparative drug screening, using curated libraries of hiPSC lines from different donors, can help to improve the delivery of safe new drugs suitable for a broad range of genetic backgrounds and sexual diversity within human populations.

cell biology↗

Cancer cells co-evolve with retrotransposons to mitigate viral mimicry

Overexpression of repetitive elements is an emerging hallmark of human cancers1. Diverse repeats can mimic viruses by replicating within the cancer genome through retrotransposition, or presenting pathogen-associated molecular patterns (PAMPs) to the pattern recognition receptors (PRRs) of the innate immune system2-5. Yet, how specific repeats affect tumor evolution and shape the tumor immune microenvironment (TME) in a pro- or anti-tumorigenic manner remains poorly defined. Here, we integrate whole genome and total transcriptome data from a unique autopsy cohort of multiregional samples collected in pancreatic ductal adenocarcinoma (PDAC) patients, into a comprehensive evolutionary analysis. We find that more recently evolved Short Interspersed Nuclear Elements (SINE), a family of retrotransposable repeats, are more likely to form immunostimulatory double-strand RNAs (dsRNAs). Consequently, younger SINEs are strongly co-regulated with RIG-I like receptor associated type-I interferon genes but anti-correlated with pro-tumorigenic macrophage infiltration. We discover that immunostimulatory SINE expression in tumors is regulated by either Long Interspersed Nuclear Elements 1 (LINE1/L1) mobility or ADAR1 activity in a TP53 mutation dependent manner. Moreover, L1 retrotransposition activity tracks with tumor evolution and is associated with TP53 mutation status. Altogether, our results suggest pancreatic tumors actively evolve to modulate immunogenic SINE stress and induce pro-tumorigenic inflammation. Our integrative, evolutionary analysis therefore illustrates, for the first time, how dark matter genomic repeats enable tumors to co-evolve with the TME by actively regulating viral mimicry to their selective advantage.

cancer biology↗

Aird-ComboComp: A combinable compressor framework with a dynamic-decider for lossy mass spectrometry data compression

Mass spectrum (MS) data volumes increase with an improved ion acquisition ratio and a highly accurate mass spectrometer. However, the most widely used data format, mzML, does not take advantage of compression methods and improved read performances. Several compression algorithms have been proposed in recent years, and they consider a number of factors, including, numerical precision, metadata read strategies and the compression performance. Due to limited compression ratio, the high-throughput MS data format is still quite large. High bandwidth and memory requirements severely limit the applicability of MS data analysis in cloud and mobile computing. ComboComp is a comprehensive improvement to the Aird data format. Instead of using the general-purpose compressor directly, ComboComp uses two integer-purpose compressors and four general-purpose compressors, and obtains the best compression combination with a dynamic decider, achieving the most balanced compression ratio among all the numerous varieties of compressors. ComboComp supports a seamless extension of the new integer and generic compressors, making it an evolving compression framework. The improvement of compression rate and decoding speed greatly reduces the cost of data exchange and real-time decompression, and effectively reduces the hardware requirements of MS data analysis. Analyzing mass spectrum data on IoT devices can be useful in real-time quality control, decentralized analysis, collaborative auditing, and other scenarios. We tested ComboComp on 11 datasets generated by commonly used MS instruments. Compared with Aird-ZDPD, the compression size can be reduced by an average of 12.9%. The decompression speed is increased by an average of 27.1%. The average compression time is almost the same as that of ZDPD. The high compression rate and decoding speed make the Aird format effective for data analysis on small memory devices. This will enable MS data to be processed normally even on IoT devices in the future. We provide SDKs in three languages, Java, C# and Python, which offer optimized interfaces for the various acquisition modes. All the SDKs can be found on Github: https://github.com/CSi-Studio/Aird-SDK.

bioinformatics↗

Protein Engineering for Thermostability through Deep Evolution

Protein engineering for increased thermostability through iterative mutagenesis and high throughput screening is labor-intensive, expensive and inefficient. Here, we developed a deep evolution (DeepEvo) strategy to engineer protein thermostability through global sequence generation and selection using deep learning models. We firstly constructed a thermostability selector based on a protein language model to extract thermostability-related features in high-dimensional latent spaces of protein sequences with high temperature tolerance. Subsequently, we constructed a variant generator based on a generative adversarial network to create protein sequences containing the desirable function with more than 50% accuracy. Finally, the generator and selector were utilized to iteratively improve the performance of DeepEvo on the model protein glyceraldehyde-3-phosphate dehydrogenase (G3PDH), whereby 8 highly thermostable variants were obtained from only 30 generated sequences, demonstrating the high efficiency of DeepEvo for the engineering of protein thermostability.

bioinformatics↗

Plasma-free samples for transcriptomic analysis: a potential alternative to whole blood samples

RNA sequencing (RNAseq) technology has become increasingly important in precision medicine and clinical diagnostics and emerged as a powerful tool for identifying protein-coding genes, performing differential gene analysis, and inferring immune cell composition. Human peripheral blood samples are widely used for RNAseq, providing valuable insights into individual biomolecular information. Blood samples can be classified as whole blood (WB), plasma, serum, and remaining sediment samples, including plasma-free blood (PFB) and serum-free blood (SFB) samples. However, the feasibility of using PFB and SFB samples for transcriptome analysis remains unclear. In this study, we aimed to assess the viability of employing PFB or SFB samples as substitute RNA sources in transcriptomic analysis and performed a comparative analysis of WB, PFB, and SFB samples for different applications. Our results revealed that PFB samples exhibit greater similarity to WB samples in terms of protein-coding gene expression patterns, differential expression gene profiling, and immunological characterizations, suggesting that PFB can be a viable alternative for transcriptomic analysis. This contributes to the optimization of blood sample utilization and the advancement of precision medicine research.

bioinformatics↗