Sequence Tags Research Articles

Analysis of Culturable Bacterial Diversity of Pangong Tso Lake via a 16S rRNA Tag Sequencing Approach.

The Pangong Tso lake is a high-altitude freshwater habitat wherein the resident microbes experience unique selective pressures, i.e., high radiation, low nutrient content, desiccation, and temperature extremes. Our study attempts to analyze the diversity of culturable bacteria by applying a high-throughput amplicon sequencing approach based on long read technology to determine the spectrum of bacterial diversity supported by axenic media. The phyla Pseudomonadota, Bacteriodetes, and Actinomycetota were retrieved as the predominant taxa in both water and sediment samples. The genera Hydrogenophaga and Rheinheimera, Pseudomonas, Loktanella, Marinomonas, and Flavobacterium were abundantly present in the sediment and water samples, respectively. Low nutrient conditions supported the growth of taxa within the phyla Bacteriodetes, Actinomycetota, and Cyanobacteria and were biased towards the selection of Pseudomonas, Hydrogenophaga, Bacillus, and Enterococcus spp. Our study recommends that media formulations can be finalized after analyzing culturable diversity through a high-throughput sequencing effort to retrieve maximum species diversity targeting novel/relevant taxa.

A gene-encoded aldehyde tag repurposed from RiPP cyclophane-forming pathway

Gene-encoded aldehyde tag technology has been widely utilized in protein bioorthogonal chemistry and biotechnological application. Herein, we report utilization of the promiscuous rSAM cyclophane synthase SjiB involved in triceptide biosynthesis as a dedicated and highly efficient formylglycine synthase. The new aldehyde tag sequence in this system, YQSSI, is biosynthetically orthogonal to the known aldehyde tag (C/S)x(P/A)xR. The potential use of SjiB/YQSSI aldehyde tag system was further validated in fluorescent labelling of model proteins.

Responses of peritubular macrophages and the testis transcriptome profiles of peripubertal and adult rodents exposed to an acute dose of MEHP.

Exposure of rodents to mono-(2-ethylhexyl) phthalate (MEHP) is known to disrupt the blood-testis barrier and cause testicular germ cell apoptosis. Peritubular macrophages (PTMφ) are a newly identified type of testicular macrophage that aggregates near the spermatogonial stem cell niche. We have previously reported that MEHP exposure increased the numbers of PTMφs by 6-fold within the testis of peripubertal rats. The underlying mechanism(s) accounting for this change in PTMφs and its biological significance is unknown. This study investigates if MEHP-induced alterations in PTMφs occur in rodents (PND 75 adult rats and PND 26 peripubertal mice) that are known to be less sensitive to MEHP-induced testicular toxicity. Results show that adult rats have a 2-fold higher basal level of PTMφ numbers than species-matched peripubertal animals, but there was no significant increase in PTMφ numbers after MEHP exposure. Peripubertal mice have a 5-fold higher basal level of PTMφ compared with peripubertal rats but did not exhibit increases in number after MEHP exposure. Further, the interrogation of the testis transcriptome was profiled from both the MEHP-responsive peripubertal rats and the less sensitive rodents via 3' Tag sequencing. Significant changes in gene expression were observed in peripubertal rats after MEHP exposure. However, adult rats showed lesser changes in gene expression, and peripubertal mice showed only minor changes. Collectively, the data show that PTMφ numbers are associated with the sensitivity of rodents to MEHP in an age- and species-dependent manner.

A closed translocation channel in the substrate-free AAA+ ClpXP protease diminishes rogue degradation

AAA+ proteases degrade intracellular proteins in a highly specific manner. E. coli ClpXP, for example, relies on a C-terminal ssrA tag or other terminal degron sequences to recognize proteins, which are then unfolded by ClpX and subsequently translocated through its axial channel and into the degradation chamber of ClpP for proteolysis. Prior cryo-EM structures reveal that the ssrA tag initially binds to a ClpX conformation in which the axial channel is closed by a pore-2 loop. Here, we show that substrate-free ClpXP has a nearly identical closed-channel conformation. We destabilize this closed-channel conformation by deleting residues from the ClpX pore-2 loop. Strikingly, open-channel ClpXP variants degrade non-native proteins lacking degrons faster than the parental enzymes in vitro but degraded GFP-ssrA more slowly. When expressed in E. coli, these open channel variants behave similarly to the wild-type enzyme in assays of filamentation and phage-Mu plating but resulted in reduced growth phenotypes at elevated temperatures or when cells were exposed to sub-lethal antibiotic concentrations. Thus, channel closure is an important determinant of ClpXP degradation specificity.

Development and Validation of Gene-Based SSR Markers in the Genus Mesembryanthemum.

Bioinformatics tools have been employed for the direct development of gene-based simple sequence repeat (SSR) markers. Through the analysis of 28,056 Mesembryanthemum expressed sequence tag (EST) sequences, a total of 5,851 ESTs containing SSRs were identified, amounting to approximately 17.07 Mb. Among these, 938 EST sequences harbored more than one SSR marker, and 788 EST-SSR sequences were found in compound form. The most prevalent types of SSR motifs were mononucleotide repeats (MNRs), accounting for 44%, followed by di-nucleotide repeats (DNRs) at 37%, and trinucleotide repeats (TNRs) at 16%. Notably, TNR or longer SSR motifs primarily consisted of shorter repeat lengths, with only 51 motifs containing 10 or more repeats. The BLASTX analysis successfully assigned functions to 4,623 (79%) of the EST sequences. Among the developed primer sets, 21 primers amplified a total of 65 alleles, with primer PMA79 EST-SSR exhibiting the maximum of six alleles. The polymorphic information content (PIC) values ranged from 0 to 0.76, with a mean of 0.47. The marker index (MI) and discriminating power (D) values reached 0.66 (primer PMA63) and 0.95 (primer PMA20), respectively. Utilizing the unweighted pair group method with arithmetic mean (UPGMA), a dendrogram was constructed, successfully segregating the 24 Mesembryanthemum genotypes into three distinct clusters, with a similarity coefficient ranging from 0.96 to 0.38. In this study, we have developed a total of 83 EST-SSR primer pairs specific to the Mesembryanthemum genus. These newly developed EST-SSRs will serve as valuable tools for researchers, particularly molecular breeders, enabling gene-based identification and trait selection through marker-assisted breeding approaches.

Design of Tandem Epitope Vaccine Against White Spot Syndrome Virus

White spot syndrome virus (WSSV) has long been a major threat on shrimp industry, but there is always a lack of effective prevention and control methods. Vaccines are widely regarded as the safest and most effective methods for preventing WSSV, and some main envelope proteins have showed this potential. In order to combine the antigenicity of these proteins together for better vaccine performance, in this study a strategy commonly used in vertebrates was tried in shrimp. The dominant epitopes of five envelope proteins VP19, VP24, VP26, VP28 and VP41A were predicted and combined for tandem epitope vaccine design by bioinformatics methods, the designed vaccine gene was chemically synthesized and expressed in Escherichia coli, then the recombinant peptide was purified for function evaluation in shrimp. The results showed that the designed peptide had good flexibility, hydrophily and antigenicity with all the epitope regions accessible; the synthesized gene was linked with the tag sequence and successfully expressed in BL21(DE3), and the purified fusion peptide showed a positive effect in WSSV prevention. This research provided a promising method to design vaccines against WSSV, and further work in genetic engineering should be done so as to make it operable for application in shrimp farm.

ERRα promotes glycolytic metabolism and targets the NLRP3/caspase-1/GSDMD pathway to regulate pyroptosis in endometrial cancer

BackgroundTumor cells can resist chemotherapy-induced pyroptosis through glycolytic reprogramming. Estrogen-related receptor alpha (ERRα) is a central regulator of cellular energy metabolism associated with poor cancer prognosis. Herein, we refine the oncogenic role of ERRα in the pyroptosis pathway and glycolytic metabolism.MethodsThe interaction between ERRα and HIF-1α was verified using co-immunoprecipitation. The transcriptional binding sites of ERRα and NLRP3 were confirmed using dual-luciferase reporter assay and cleavage under targets and tagmentation (CUT&Tag). Flow cytometry, transmission electron microscopy, scanning electron microscopy, cell mito stress test, and extracellular acidification rate analysis were performed to investigate the effects of ERRα on the pyroptosis pathway and glycolytic metabolism. The results of these experiments were further confirmed in endometrial cancer (EC)-derived organoids and nude mice. In addition, the expression of ERRα-related pyroptosis genes was analyzed using The Cancer Genome Atlas and Gene Expression Omnibus database.ResultsTriggered by a hypoxic microenvironment, highly expressed ERRα could bind to the promoter of NLRP3 and inhibit caspase-1/GSDMD signaling, which reduced inflammasome activation and increased pyroptosis resistance, thereby resulting in the resistance of cancer cells to cisplatin. Moreover, ERRα activated glycolytic rate-limiting enzyme to bridge glycolytic metabolism and pyroptosis in EC. This phenomenon was further confirmed in EC-derived organoids and nude mice. CUT & Tag sequencing and The Cancer Genome Atlas database analysis showed that ERRα participated in glycolysis and programmed cell death, which resulted in EC progression.ConclusionsERRα inhibits pyroptosis in an NLRP3-dependent manner and induces glycolytic metabolism, resulting in cisplatin resistance in EC cells.

Efficient expression and purification of tag-free recombinant human procalcitonin (hPCT) with precise sequence in E.coli

We present an efficient method for expression and purification of recombinant human procalcitonin (hPCT) in E. coli T7 express LysY/Iq cells, ensuring precise N- and C-terminal amino acid sequences. Our method involves fusing codon-optimized cDNA with two distinct tag sequences: eXact tag and chitin binding domain (CBD) tag. To purify the protein, we employ a two-step affinity chromatography process. Firstly, we utilize the N-terminal Profinity eXact tag and purify the protein through Profinity eXact-affinity column chromatography using a resin on which a mutant subtilisin protease was immobilized. The eXact tag was removed by adding NaF to activate the enzyme. Subsequently, the digested sample containing C-terminal CBD tag is directly loaded for the second step of chitin affinity chromatography. Elution is achieved through dithiothreitol (DTT)-catalyzed self-cleavage of the intein sequence from the fusion protein. As a result, the target protein is selectively recovered in the flow-through, completely tag-free, with a purity exceeding 95%. To ensure high purity and eliminate potential contaminants, we effectively remove E. coli host DNA and endotoxins through a combination of streptomycin sulfate, Triton X-114, and ammonium sulfate treatment. The exceptional level of purity obtained eliminates the need for further purification steps in most applications. This highly purified hPCT can be used as a calibrator in procalcitonin or calcitonin immunoassays. Notably, our approach effectively manages small peptides that are prone to degradation by E. coli host proteases, offering a robust solution for various research and application requirements.

Identification of microRNAs involved in ectomycorrhizal formation in Populus tomentosa.

The majority of woody plants are able to form ectomycorrhizal (ECM) symbioses with fungi. During symbiotic development, plants undergo a complex re-programming process involving a series of physiological and morphological changes. MicroRNAs (miRNAs) are important components of the regulatory network underlying symbiotic development. To elucidate the mechanisms of miRNAs and miRNA-mediated mRNA cleavage during symbiotic development, we conducted high-throughput sequencing of small RNAs and degradome tags from roots of Populus tomentosa inoculated with Cenococcum geophilum. This process led to the annotation of 51 differentially expressed miRNAs between non-mycorrhizal and mycorrhizal roots of P. tomentosa, including 13 novel miRNAs. Increased or decreased accumulation of several novel and conserved miRNAs in ECM roots, including miR162, miR164, miR319, miR396, miR397, miR398, novel-miR44 and novel-miR47, suggests essential roles for these miRNAs in ECM formation. The degradome analysis identified root transcripts as miRNA-mediated mRNA cleavage targets, which was confirmed using real-time quantitative PCR. Several of the identified miRNAs and corresponding targets are involved in arbuscular mycorrhizal symbioses. In summary, increased or decreased accumulation of specific miRNAs and miRNA-mediated cleavage of symbiosis-related genes indicate that miRNAs play important roles in the regulatory network underlying symbiotic development.

Sequence tagging with a rethinking structure for joint entity and relation extraction

Sequence tagging with a rethinking structure for joint entity and relation extraction

3D organization of regulatory elements for transcriptional regulation in Arabidopsis

BackgroundAlthough spatial organization of compartments and topologically associating domains at large scale is relatively well studied, the spatial organization of regulatory elements at fine scale is poorly understood in plants.ResultsHere we perform high-resolution chromatin interaction analysis using paired-end tag sequencing approach. We map chromatin interactions tethered with RNA polymerase II and associated with heterochromatic, transcriptionally active, and Polycomb-repressive histone modifications in Arabidopsis. Analysis of the regulatory repertoire shows that distal active cis-regulatory elements are linked to their target genes through long-range chromatin interactions with increased expression of the target genes, while poised cis-regulatory elements are linked to their target genes through long-range chromatin interactions with depressed expression of the target genes. Furthermore, we demonstrate that transcription factor MYC2 is critical for chromatin spatial organization, and propose that MYC2 occupancy and MYC2-mediated chromatin interactions coordinately facilitate transcription within the framework of 3D chromatin architecture. Analysis of functionally related gene-defined chromatin connectivity networks reveals that genes implicated in flowering-time control are functionally compartmentalized into separate subdomains via their spatial activity in the leaf or shoot apical meristem, linking active mark- or Polycomb-repressive mark-associated chromatin conformation to coordinated gene expression.ConclusionThe results reveal that the regulation of gene transcription in Arabidopsis is not only by linear juxtaposition, but also by long-range chromatin interactions. Our study uncovers the fine scale genome organization of Arabidopsis and the potential roles of such organization in orchestrating transcription and development.

DeepChIA-PET: Accurately predicting ChIA-PET from Hi-C and ChIP-seq with deep dilated networks.

Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) can capture genome-wide chromatin interactions mediated by a specific DNA-associated protein. The ChIA-PET experiments have been applied to explore the key roles of different protein factors in chromatin folding and transcription regulation. However, compared with widely available Hi-C and ChIP-seq data, there are not many ChIA-PET datasets available in the literature. A computational method for accurately predicting ChIA-PET interactions from Hi-C and ChIP-seq data is needed that can save the efforts of performing wet-lab experiments. Here we present DeepChIA-PET, a supervised deep learning approach that can accurately predict ChIA-PET interactions by learning the latent relationships between ChIA-PET and two widely used data types: Hi-C and ChIP-seq. We trained our deep models with CTCF-mediated ChIA-PET of GM12878 as ground truth, and the deep network contains 40 dilated residual convolutional blocks. We first showed that DeepChIA-PET with only Hi-C as input significantly outperforms Peakachu, another computational method for predicting ChIA-PET from Hi-C but using random forests. We next proved that adding ChIP-seq as one extra input does improve the classification performance of DeepChIA-PET, but Hi-C plays a more prominent role in DeepChIA-PET than ChIP-seq. Our evaluation results indicate that our learned models can accurately predict not only CTCF-mediated ChIA-ET in GM12878 and HeLa but also non-CTCF ChIA-PET interactions, including RNA polymerase II (RNAPII) ChIA-PET of GM12878, RAD21 ChIA-PET of GM12878, and RAD21 ChIA-PET of K562. In total, DeepChIA-PET is an accurate tool for predicting the ChIA-PET interactions mediated by various chromatin-associated proteins from different cell types.

Advancements in Named Entity Recognition using Deep Learning Techniques: A Comprehensive Study on Emerging Trends

Because of the amount of computer-processable text material and processing hardware, deep learning architecture has been the focus of knowledge projects. The task of named entity recognition in natural language processing is no exception. Because of the volume of text material that computers can process and their processing capability, knowledge projects are now focusing on deep learning architecture. Named entity recognition, is a frequently occurring task in natural language processing. Deep learning models, particularly recurrent neural net- works (RNNs) and their variations such as gated recurrent units (GRUs) and long short-term memory (LSTM) , have revolutionised natural language pro- cessing (NER) by capturing intricate contextual connections. These models can accurately forecast the borders and types of named entities because they can effectively capture the sequential and hierarchical patterns inside text. However, using deep learning in NER is a challenging task in itself. Annotated training data is critical for building reliable models, but getting labelled data for all item kinds and domains can be time-consuming. To solve this difficulty, transfer learn- ing and domain adaptation strategies have arisen, using pre-trained models and adapting them to various domains or target tasks. This paper looks at recent deep learning methods for NER and how they evolved from older linear learning approaches. It also analyses the status of activities that are either upstream or downstream of NER, such as sequence tagging and entity linking, among other things

Inhibitor AN3661 reveals biological functions of Arabidopsis CLEAVAGE and POLYADENYLATION SPECIFICITY FACTOR 73.

Cleavage and polyadenylation specificity factor (CPSF) is a protein complex that plays an essential biochemical role in mRNA 3'-end formation, including poly(A) signal recognition and cleavage at the poly(A) site. However, its biological functions at the organismal level are mostly unknown in multicellular eukaryotes. The study of plant CPSF73 has been hampered by the lethality of Arabidopsis (Arabidopsis thaliana) homozygous mutants of AtCPSF73-I and AtCPSF73-II. Here, we used poly(A) tag sequencing to investigate the roles of AtCPSF73-I and AtCPSF73-II in Arabidopsis treated with AN3661, an antimalarial drug with specificity for parasite CPSF73 that is homologous to plant CPSF73. Direct seed germination on an AN3661-containing medium was lethal; however, 7-d-old seedlings treated with AN3661 survived. AN3661 targeted AtCPSF73-I and AtCPSF73-II, inhibiting growth through coordinating gene expression and poly(A) site choice. Functional enrichment analysis revealed that the accumulation of ethylene and auxin jointly inhibited primary root growth. AN3661 affected poly(A) signal recognition, resulted in lower U-rich signal usage, caused transcriptional readthrough, and increased the distal poly(A) site usage. Many microRNA targets were found in the 3' untranslated region lengthened transcripts; these miRNAs may indirectly regulate the expression of these targets. Overall, this work demonstrates that AtCPSF73 plays important part in co-transcriptional regulation, affecting growth, and development in Arabidopsis.

Abstract A054: Accurate prediction of cohesin-mediated 3D genome organization using 2D chromatin features

Abstract The three-dimensional (3D) genome organization influences diverse nuclear processes. Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and High-throughput chromatin conformation capture (Hi-C) are powerful methods used to study the 3D genome organization. However, these two experiments are costly, time-consuming, require tens to hundreds of millions of cells, and challenging to optimize and analyze. Predicting ChIA-PET/Hi-C data using cheaper ChIP-Seq data and other easily obtainable features is a useful alternative. Also, it is well-established that the cohesin protein complex is a key determinant of 3D genome organization. Considering this, we present Chromatin Interaction Predictor (ChIPr), a suite of regression models based on deep neural networks (DNN), random forest, and gradient boosting. ChIPr predicts cohesin-mediated chromatin interaction strength between any two given loci in the genome. It was trained mainly using two top-tiered ENCODE cell lines GM12878 and K562 and tested on other cell lines (H1 and HepG2). Comprehensive tests showed that ChIPr predictions correlated well with the original ChIA-PET data at the peak-level resolution and at bin sizes 25kb and 5kb. In addition, ChIPr accurately captured most of the cell-type-dependent loops identified by both, ChIA-PET and Hi-C data, respectively. Extensive feature testing highlighted genomic distance and RAD21 (a cohesin component) ChIP-Seq signals as the most important inputs contributing to ChIPr, in determining the chromatin interaction strength. A standard ChIPr model requires three experimental inputs: ChIP-Seq signals for RAD21, H3K27ac (enhancer/active chromatin mark), and H3K27me3 (inactive chromatin mark). While a reduced model requires a single experiment input: ChIP-Seq signals for RAD21 and performs equally well. Additionally, the use of ChIPr was further extended to predict the contact maps for several prostate cancer (PCa) cell lines whose ChIA-PET data were not available on the ENCODE portal, for instance, RWPE1 and VCaP. We generated the necessary ChIP-seq data for these cell lines to use as input to the model to further examine the changes in the 3D interactions of PCa driver genes and also their isolated neighbourhoods and decipher useful biological insights about the gene regulatory networks involved. Integrative analysis revealed novel insights into the role of CTCF motif, its orientation, and CTCF binding on the prevalence and strength of cohesin-mediated chromatin interactions (~50% - 80% of the RAD21 interactions were enriched with CTCF, < 15% of the interactions had no CTCF ChIP-seq binding in both of the two peaks). Lastly, we also noticed a subset of RAD21 interactions with CTCF binding in only one or none of the two anchor peaks, which were significantly enriched with enhancers. Taken together, this study outlines the general features of genome folding and opens new avenues to analyze spatial genome organization in specimens with limited cell numbers. Citation Format: Khyati Chandratre. Accurate prediction of cohesin-mediated 3D genome organization using 2D chromatin features [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A054.

Tetrameric Antibody Complexes and Affinity Tag Peptides for the Selective Immobilization and Imaging of Single Quantum Dots.

Colloidal semiconductor quantum dots (QDs) are of widespread interest as fluorescent labels for bioanalysis and imaging applications. Single-particle measurements have proven to be a very powerful tool for better understanding the fundamental properties and behaviors of QDs and their bioconjugates; however, a recurring challenge is the immobilization of QDs in a solution-like environment that minimizes interactions with a bulk surface. Immobilization strategies for QD-peptide conjugates are particularly underdeveloped within this context. Here, we present a novel strategy for the selective immobilization of single QD-peptide conjugates using a combination of tetrameric antibody complexes (TACs) and affinity tag peptides. A glass substrate is modified with an adsorbed layer of concanavalin A (ConA) that binds a subsequent layer of dextran that minimizes nonspecific binding. A TAC with anti-dextran and anti-affinity tag antibodies binds to the dextran-coated glass surface and to the affinity tag sequence of QD-peptide conjugates. The result is spontaneous and sequence-selective immobilization of single QDs without any chemical activation or cross-linking. Controlled immobilization of multiple colors of QDs is possible using multiple affinity tag sequences. Experiments confirmed that this approach positions the QD away from the bulk surface. The method supports real-time imaging of binding and dissociation, measurements of Förster resonance energy transfer (FRET), tracking of dye photobleaching, and detection of proteolytic activity. We anticipate that this immobilization strategy will be useful for studies of QD-associated photophysics, biomolecular interactions and processes, and digital assays.

Uniting Multi-Scale Local Feature Awareness and the Self-Attention Mechanism for Named Entity Recognition

In recent years, a huge amount of text information requires processing to support the diagnosis and treatment of diabetes in the medical field; therefore, the named entity recognition of diabetes (DNER) is giving rise to the popularity of this research topic within this particular field. Although the mainstream methods for Chinese medical named entity recognition can effectively capture global context information, they ignore the potential local information in sentences, and hence cannot extract the local context features through an efficient framework. To overcome these challenges, this paper constructs a diabetes corpus and proposes the RMBC (RoBERTa Multi-scale CNN BiGRU Self-attention CRF) model. This model is a named entity recognition model that unites multi-scale local feature awareness and the self-attention mechanism. This paper first utilizes RoBERTa-wwm to encode the characters; then, it designs a local context-wise module, which captures the context information containing locally important features by fusing multi-window attention with residual convolution at the multi-scale and adds a self-attention mechanism to address the restriction of the bidirectional gated recurrent unit (BiGRU) capturing long-distance dependencies and to obtain global semantic information. Finally, conditional random fields (CRF) are relied on to learn of the dependency between adjacent tags and to obtain the optimal tag sequence. The experimental results on our constructed private dataset, termed DNER, along with two benchmark datasets, demonstrate the effectiveness of the model in this paper.

Identification of heat shock protein hsp70 family genes from Rana amurensis and its expression profiles upon infection

Heat shock proteins (HSPs) widely exist in all organisms, the structures of which are usually extraordinarily conservative. They are also well-known stress proteins that are involved in response to physical, chemical and biological stresses. HSP70 is an important member of the HSPs family. In order to study the roles of amphibians HSP70 during infection, the cDNA sequence of Rana amurensis hsp70 family genes were cloned by homologous cloning method. The sequence characteristics, three-dimensional structure and genetic relationship of Ra-hsp70s were analyzed by bioinformatics methods. The expression profiles under bacterial infection were also analyzed by real-time quantitative PCR (qRT-PCR). Expression and localization of HSP70 protein were tested by immunohistochemical techniques. The results showed that three conservative tag sequences of HSP70 family, HSPA5, HSPA8 and HSPA13, were found in HSP70. Phylogenetic tree analysis indicated four members are distributed in four different branches, and members with the same subcellular localization motif are distributed in the same branch. The relative expression levels of the mRNA of four members were all significantly upregulated (P < 0.01) upon infection, but the time for up-regulating the expression levels were diverse in different tissues. The immunohistochemical analysis showed that HSP70 was expressed to different degrees in the cytoplasm of liver, kidney, skin and stomach tissue. The four members of Ra-hsp70 family have ability to respond bacterial infection to varying degrees. Therefore, it was proposed that they are involved in biological processes against pathogen and play different biological functions. The study provides a theoretical basis for functional studies of HSP70 gene in amphibians.

Abstract 6619: Virtual staining enabled combined morphological and spatial transcriptomic analysis of individual malignant B cells and local tumor microenvironments

Abstract B-cell lymphomas, commonly classified by histological presentation and B-cell lineage, are in fact heterogeneous diseases with respect to gene expression and tumor microenvironment. Certain lymphomas, such as Hodgkin and T-cell rich B-cell lymphoma, may contain fewer than 1% malignant cells in a largely inflammatory background. These rare malignant cells have unique interactions with local tumor microenvironments (TME), in some cases driving distinct gene expression patterns for individual B-cells. This presents a challenging fundamental biology landscape, which can create uncertainty in directing patient care or developing new therapies. The lack of tools allowing subtyping of malignant B-cells while simultaneously preserving the context of local TMEs and providing deep spatial transcriptomic sequencing further complicates analysis. Here we have developed an integrated, single-slide workflow of virtual H&amp;E staining using the inherent tissue autofluorescence (PictorLabs, Los Angeles, CA) of formalin-fixed, paraffin embedded lymphoma tissue sections on the GeoMx® Digital Spatial Profiler (Nanostring, Seattle, WA) combined with spatial expression analysis of 1,800 genes using the Cancer Transcriptome Atlas (CTA) panel. The H&amp;E virtual staining allows for the assessment of B-cell lymphoma subtypes, identification and phenotyping of malignant B-cells and the immediately proximal (within 30µm) TME regions by a certified pathologist. These regions of interest (ROI) are spatially profiled for transcriptional expression determined by NGS sequencing of the RNA target specific DNA oligo tags. We benchmarked our system by analyzing four lymphoma cases: Nodular sclerosis classical Hodgkin, Nodular lymphocyte-predominant Hodgkin, T-cell/histiocyte rich large B-cell, and Diffuse large B-cell lymphomas. Using virtual H&amp;E staining on the GeoMx Digital Spatial Profiler platform, a pathologist correctly identified the diagnosis and subtype based on the morphology. Regions of inflammatory B- and T-cells could be distinguished from lymphoma cells on virtual staining, allowing subset segregation for digital transcriptional expression profiling with the GeoMx CTA panel. Additionally, background TME more distant to B-cell lymphoma as well as regions of high T-cell infiltration were selected for profiling. Analysis of the ROIs revealed distinct transcriptional profiles of malignant B-cells (including cell-of-origin signature), the signaling contributions of local TMEs (versus non-adjacent regions) and confirmed that the expression patterns are further influenced by the presence of T-cell infiltration. Citation Format: Michael E. Kallen, Alyssa Rosenbloom, Zihang Fang, Raymond Kozikowski, Yair Rivenson, Kevin de Haan, Serge Alexanian, Mark Conner, Daniel Newhouse, Felicia New, Yan Liang, Kyla Teplitz, Joachim Schmid, Jaemyeong Jung. Virtual staining enabled combined morphological and spatial transcriptomic analysis of individual malignant B cells and local tumor microenvironments [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6619.

Haplotype mapping of H3K27me3-associated chromatin interactions defines topological regulation of gene silencing in rice

Histone modification H3K27me3 is an important chromatin mark that plays vital roles in repressing expression of developmental genes. Here, we construct high-resolution 3D genome maps using long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and characterize H3K27me3-associated chromatin interactions in an elite rice hybrid, Shanyou 63. We find that many H3K27me3-marked regions may function as silencer-like regulatory elements. The silencer-like elements can come into proximity with distal target genes via forming chromatin loops in 3D space of the nuclei, regulating gene silencing and plant traits. Natural and induced deletion of silencers upregulate expression of distal connected genes. Furthermore, we identify extensive allele-specific chromatin loops. We find that genetic variations alter allelic chromatin topology, thus modulating allelic gene imprinting in rice hybrids. In conclusion, the characterization of silencer-like regulatory elements and haplotype-resolved chromatin interaction maps provide insights into the understanding of molecular mechanisms underlying allelic gene silencing and plant trait controlling.