Sequence-Signature Optimization Enables Improved Identification of Human HV6-1-Derived Class Antibodies That Neutralize Diverse Influenza A Viruses

Sequence signatures of multidonor broadly neutralizing influenza antibodies can be used to quantify the prevalence of B cells with virus-neutralizing potential to accelerate development of broadly protective vaccine strategies. Antibodies of the same class share similar recognition modes and developmental pathways, and several antibody classes have been identified that neutralize diverse group 1- and group 2-influenza A viruses and have been observed in multiple human donors. One such multidonor antibody class, the HV6-1-derived class, targets the stem region of hemagglutinin with extraordinary neutralization breadth. Here, we use an iterative process to combine informatics, biochemical, and structural analyses to delineate an improved sequence signature for HV6-1-class antibodies. Based on sequence and structure analyses of known HV6-1 class antibodies, we derived a more inclusive signature (version 1), which we used to search for matching B-cell transcripts from published next-generation sequencing datasets of influenza vaccination studies. We expressed selected antibodies, evaluated their function, and identified amino acid-level requirements from which to refine the sequence signature (version 2). The cryo-electron microscopy structure for one of the signature-identified antibodies in complex with hemagglutinin confirmed motif recognition to be similar to known HV6-1-class members, MEDI8852 and 56.a.09, despite differences in recognition-loop length. Threading indicated the refined signature to have increased accuracy, and signature-identified heavy chains, when paired with the light chain of MEDI8852, showed neutralization comparable to the most potent members of the class. Incorporating sequences of additional class members thus enables an improved sequence signature for HV6-1-class antibodies, which can identify class members with increased accuracy.

Application of alternative de novo motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites

The most popular model for the search of ChIP-seq data for transcription factor binding sites (TFBS) is the positional weight matrix (PWM). However, this model does not take into account dependencies between nucleotide occurrences in different site positions. Currently, two recently proposed models, BaMM and InMoDe, can do as much. However, application of these models was usually limited only to comparing their recognition accuracies with that of PWMs, while none of the analyses of the co-prediction and relative positioning of hits of different models in peaks has yet been performed. To close this gap, we propose the pipeline called MultiDeNA. This pipeline includes stages of model training, assessing their recognition accuracy, scanning ChIP-seq peaks and their classif ication based on scan results. We applied our pipeline to 22 ChIP-seq datasets of TF FOXA2 and considered PWM, dinucleotide PWM (diPWM), BaMM and InMoDe models. The combination of these four models allowed a signif icant increase in the fraction of recognized peaks compared to that for the sole PWM model: the increase was 26.3 %. The BaMM model provided the main contribution to the recognition of sites. Although the major fraction of predicted peaks contained TFBS of different models with coincided positions, the medians of the fraction of peaks containing the predictions of sole models were 1.08, 0.49, 4.15 and 1.73 % for PWM, diPWM, BaMM and InMoDe, respectively. Thus, FOXA2 BSs were not fully described by only a sole model, which indicates theirs heterogeneity. We assume that the BaMM model is the most successful in describing the structure of the FOXA2 BS in ChIP-seq datasets under study.

Fra-1 regulates its target genes via binding to remote enhancers without exerting major control on chromatin architecture in triple negative breast cancers

The ubiquitous family of dimeric transcription factors AP-1 is made up of Fos and Jun family proteins. It has long been thought to operate principally at gene promoters and how it controls transcription is still ill-understood. The Fos family protein Fra-1 is overexpressed in triple negative breast cancers (TNBCs) where it contributes to tumor aggressiveness. To address its transcriptional actions in TNBCs, we combined transcriptomics, ChIP-seqs, machine learning and NG Capture-C. Additionally, we studied its Fos family kin Fra-2 also expressed in TNBCs, albeit much less. Consistently with their pleiotropic effects, Fra-1 and Fra-2 up- and downregulate individually, together or redundantly many genes associated with a wide range of biological processes. Target gene regulation is principally due to binding of Fra-1 and Fra-2 at regulatory elements located distantly from cognate promoters where Fra-1 modulates the recruitment of the transcriptional co-regulator p300/CBP and where differences in AP-1 variant motif recognition can underlie preferential Fra-1- or Fra-2 bindings. Our work also shows no major role for Fra-1 in chromatin architecture control at target gene loci, but suggests collaboration between Fra-1-bound and -unbound enhancers within chromatin hubs sometimes including promoters for other Fra-1-regulated genes. Our work impacts our view of AP-1.

Nucleosome allostery in pioneer transcription factor binding

While recent experiments revealed that some pioneer transcription factors (TFs) can bind to their target DNA sequences inside a nucleosome, the binding dynamics of their target recognitions are poorly understood. Here we used the latest coarse-grained models and molecular dynamics simulations to study the nucleosome-binding procedure of the two pioneer TFs, Sox2 and Oct4. In the simulations for a strongly positioning nucleosome, Sox2 selected its target DNA sequence only when the target was exposed. Otherwise, Sox2 entropically bound to the dyad region nonspecifically. In contrast, Oct4 plastically bound on the nucleosome mainly in two ways. First, the two POU domains of Oct4 separately bound to the two parallel gyres of the nucleosomal DNA, supporting the previous experimental results of the partial motif recognition. Second, the POUSdomain of Oct4 favored binding on the acidic patch of histones. Then, simulating the TFs binding to a genomic nucleosome, theLIN28Bnucleosome, we found that the recognition of a pseudo motif by Sox2 induced the local DNA bending and shifted the population of the rotational position of the nucleosomal DNA. The redistributed DNA phase, in turn, changed the accessibility of a distant TF binding site, which consequently affected the binding probability of a second Sox2 or Oct4. These results revealed a nucleosomal DNA-mediated allosteric mechanism, through which one TF binding event can change the global conformation, and effectively regulate the binding of another TF at distant sites. Our simulations provide insights into the binding mechanism of single and multiple TFs on the nucleosome.

Genomics functional analysis and drug screening of 2019 novel coronavirus in Wuhan, China

A novel coronavirus appeared in Wuhan, China has led to major outbreaks. In the present, rapid classification of viruses, analysis of genome and screening for effective drugs are the most important tasks. In the present study, through literature review, sequence alignment, ORF identification, motif recognition, secondary and tertiary structure prediction, the whole genome of coronavirus were comprehensively analyzed. In order to find effective drugs, the parameters of binding were calculated by SeeSAR. In addition, potential miRNAs were predicted according to RNA base-pairing. After prediction by NCBI, WebMGA and GeneMark, a total of 8 credible ORFs were detected. Even the whole genome have great difference with other CoVs, each ORF has high homology with SARS-CoVs (＞90%). Furthermore, domain composition in each ORFs was also similar to SARS. In DrugBank database, only 7 potential drugs were screened based on sequence search module. Further predicted binding sites between drug and ORFs revealed that 2-(N-Morpholino)-ethanesulfonic acid could bind 1# ORF in 4 different regions ideally. Meanwhile, 2 miRNAs (miR-1307-3p and miR-3613-5p) may be able to prevent virus replication or as biomarkers. In conclusion, the novel coronavirus may have consanguinity with SARS. Drugs used to treat SARS may also be effective against the novel virus. In addition, altering miRNA expression may become a potential therapeutic schedule.

A crystal structure of a collaborative RNA regulatory complex reveals mechanisms to refine target specificity

In the Caenorhabditis elegans germline, fem-3 Binding Factor (FBF) partners with LST-1 to maintain stem cells. A crystal structure of an FBF-2/LST-1/RNA complex revealed that FBF-2 recognizes a short RNA motif different from the characteristic 9-nt FBF binding element, and compact motif recognition coincided with curvature changes in the FBF-2 scaffold. Previously, we engineered FBF-2 to favor recognition of shorter RNA motifs without curvature change (Bhat et al., 2019). In vitro selection of RNAs bound by FBF-2 suggested sequence specificity in the central region of the compact element. This bias, reflected in the crystal structure, was validated in RNA-binding assays. FBF-2 has the intrinsic ability to bind to this shorter motif. LST-1 weakens FBF-2 binding affinity for short and long motifs, which may increase target selectivity. Our findings highlight the role of FBF scaffold flexibility in RNA recognition and suggest a new mechanism by which protein partners refine target site selection.