Collection Of Transcription Factors Research Articles

Single-Cell Multiomics Analysis Reveals Potential Drivers of Response to the Anti-TIM3 Inhibitor Sabatolimab Combined with Azacitidine in MDS and CMML

Background The median survival for patients with newly diagnosed (ND) higher risk myelodysplastic syndrome (MDS) and chronic myelomonocytic leukemia (CMML) remains poor. The potential curability of MDS and CMML with allogeneic hematopoietic stem cell transplantation supports the concept of anti-tumor immunity and has led to interest in evaluating immune-based therapeutic approaches in myeloid neoplasms. The immune checkpoint molecule TIM-3 (encoded by the gene HAVCR2) is a target of interest in myeloid neoplasms given its expression on leukemic stem cells as well as several subsets of immune cells including T cells, monocytes, dendritic cells and NK cells. Sabatolimab (MBG453) is an investigational IgG4 anti-TIM-3 antibody currently under evaluation for myeloid neoplasms. In this exploratory study, we sought to characterize the effects of sabatolimab combined with the hypomethylating agent (HMA), azacitidine, on the immune landscape using single cell sequencing of samples from subjects with MDS and CMML treated with the combination from a previously reported phase 1b study (NCT03066648; Brunner et al 2022). Methods Following IRB approval, single-cell RNA sequencing (scRNA-seq) and associated proteomic cellular indexing of transcriptomes and epitopes sequencing (CITE-seq) was performed on both blood (BLD) and bone-marrow (BM) derived samples from subjects with: 1) MDS (n=3) or CMML (n=2) treated with HMA therapy alone as part of standard care; 2) ND MDS (n=5) or CMML (n=3) treated with azacitidine combined with sabatolimab; and 3) relapsed/refractory MDS (n=3) treated with sabatolimab alone. Paired BLD and BM samples as well as samples from serial treatment time points were selected whenever feasible (Fig 1). A total of 206,183 cells from BM and 172,421 cells from BLD post-quality control filtering were analyzed. Further, scRNAseq data from normal BLD(200,000 cells) and BM(240,650 cells) generated as part of the human cell atlas (https://data.humancellatlas.org/explore/projects/cc95ff89-2e68-4a08-a234-480eca21ce79) were integrated with this dataset to assist with immune cell subset characterization, enable downstream comparisons to healthy hematopoietic cells, and to help define cell subsets associated with disease states. Results In baseline samples from subjects with MDS treated with azacitidine-sabatolimab, we found that an increased baseline abundance of interferon-responsive CD8 T cells in both the BM and BLD (FDR<0.1) was associated with response to therapy. An increased baseline abundance of plasmacytoid dendritic cells and a granulocyte population also suggested an association with response to therapy. Differential gene expression analysis of baseline samples from responding versus non-responding subjects with MDS treated with azacitidine-sabatolimab showed a higher baseline expression of TNF and IFNG in BM CD8 T cells and up-regulated expression of MHC-II machinery ( HLA-DRB1, HLA-DPA1, CD74) in myeloid cell subsets in responding subjects (FDR <0.1), suggesting that pre-treatment ability of these cells to be involved in antigen-presentation may play a role in response. In subjects with CMML treated with azacitidine-sabatolimab, we observed dynamic changes in cellular abundances and gene expression when comparing baseline to post-therapy timepoints. Specifically, BM CD8 T cell subsets showed an up-regulation of cytotoxicity genes ( GZMA), interferon response genes ( IFIT2, IFITM1, IFITM2) and IL32 cytokine post-therapy (FDR <0.1). When evaluating myelomonocytic cell populations, we observed an increase in CD16 monocytes post-treatment. Additionally, dendritic cells and monocytes showed an up-regulation of interferon response genes ( IFIT1, OAS1, IFI27). Conversely, we observed a down-regulation of metallothionein genes ( MT1E, MT1G, MT2A) as well as a collection of transcription factors ( NR4A1, FOSL2, JUN, CEBPB, CEBPD), NF-κB inhibitors ( NFKBIZ, NFKBIA) and CXCL8 in the post-treatment samples (FDR <0.1). Conclusions Our study provides one of the most comprehensive evaluations of the cellular dynamics of anti-TIM3 immunotherapy in patients to date, allowing for the nomination of novel putative predictive biomarkers of response and identification of potential immunomodulatory mechanisms induced by the combination of sabatolimab with azacitidine in MDS and CMML for further future analysis.

A global search for novel transcription factors impacting the Neurospora crassa circadian clock.

Eukaryotic circadian oscillators share a common circuit architecture, a negative feedback loop in which a positive element activates the transcription of a negative one that then represses the action of the former, inhibiting its own expression. While studies in mammals and insects have revealed additional transcriptional inputs modulating the expression of core clock components, this has been less characterized in the model Neurospora crassa, where the participation of other transcriptional components impacting circadian clock dynamics remains rather unexplored. Thus, we sought to identify additional transcriptional regulators modulating the N. crassa clock, following a reverse genetic screen based on luminescent circadian reporters and a collection of transcription factors (TFs) knockouts, successfully covering close to 60% of them. Besides the canonical core clock components WC-1 and -2, none of the tested transcriptional regulators proved to be essential for rhythmicity. Nevertheless, we identified a set of 23 TFs that when absent lead to discrete, but significant, changes in circadian period. While the current level of analysis does not provide mechanistic information about how these new players modulate circadian parameters, the results of this screen reveal that an important number of light and clock-regulated TFs, involved in a plethora of processes, are capable of modulating the clockworks. This partial reverse genetic clock screen also exemplifies how the N. crassa knockout collection continues to serve as an expedite platform to address broad biological questions.

Deciphering the functional diversity of DNA-binding transcription factors in Bacteria and Archaea organisms

DNA-binding Transcription Factors (TFs) play a central role in regulation of gene expression in prokaryotic organisms, and similarities at the sequence level have been reported. These proteins are predicted with different abundances as a consequence of genome size, where small organisms contain a low proportion of TFs and large genomes contain a high proportion of TFs. In this work, we analyzed a collection of 668 experimentally validated TFs across 30 different species from diverse taxonomical classes, including Escherichia coli K-12, Bacillus subtilis 168, Corynebacterium glutamicum, and Streptomyces coelicolor, among others. This collection of TFs, together with 111 hidden Markov model profiles associated with DNA-binding TFs collected from diverse databases such as PFAM and DBD, was used to identify the repertoire of proteins putatively devoted to gene regulation in 1321 representative genomes of Archaea and Bacteria. The predicted regulatory proteins were posteriorly analyzed in terms of their genomic context, allowing the prediction of functions for TFs and their neighbor genes, such as genes involved in virulence, enzymatic functions, phosphorylation mechanisms, and antibiotic resistance. The functional analysis associated with PFAM groups showed diverse functional categories were significantly enriched in the collection of TFs and the proteins encoded by the neighbor genes, in particular, small-molecule binding and amino acid transmembrane transporter activities associated with the LysR family and proteins devoted to cellular aromatic compound metabolic processes or responses to drugs, stress, or abiotic stimuli in the MarR family. We consider that with the increasing data derived from new technologies, novel TFs can be identified and help improve the predictions for this class of proteins in complete genomes. The complete collection of experimentally characterized and predicted TFs is available at http://web.pcyt.unam.mx/EntrafDB/.

Identification of Protein-DNA Interactions Using Enhanced Yeast One-Hybrid Assays and a Semiautomated Approach.

Yeast one-hybrid assays are an in vitro gene-centered approach to map transcription factor-DNA interactions. Here we describe this method and adaptations to screen for interactions between plant transcriptional regulators and their targets. Of particular note, the use of yeast one-hybrid assays fills in an important gap in available methodologies. When one is interested in a specific biological process of interest, the yeast one-hybrid assay is the only method that allows researchers to identify upstream regulators of the biological process of interest. This technique can be also used to further validate physical protein-DNA interactions or as a hypothesis-generating tool. In this method, promoters or DNA regions of interest are cloned and transformed into yeast and tested for interaction against a collection of transcription factors (TFs). Yeast one-hybrid screens are adaptable to the question the researcher is asking and the tools and components available. In this chapter we will describe large-scale and high-throughput Y1H screening; however, this can easily be scaled down for smaller studies.

Tissue Determination Using the Animal Cap Transplant (ACT) Assay in <em>Xenopus laevis</em>

Many proteins play a dual role in embryonic development. Those that regulate cell fate determination in a specific tissue can also affect the development of a larger region of the embryo. This makes defining its role in a particular tissue difficult to analyze. For example, noggin overexpression in Xenopus laevis embryos causes the expansion of the entire anterior region, including the eye1,2. From this result, it is not known if Noggin plays a direct role in eye determination or that by causing an expansion of neural tissue, Noggin indirectly affects eye formation. Having this complex phenotype makes studying its eye-specific role in cell fate determination difficult to analyze. We have developed an assay that overcomes this problem. Taking advantage of the pluripotent nature of the Xenopus laevis animal cap 3, we have developed an assay to test the ability of gene product(s), like noggin or the eye field transcription factors (EFTFs), to transform caps into particular tissue or cell types by transplanting this tissue onto the side of the embryo 4. While we have found either Noggin protein treatment or a collection of transcription factors can determine retinal cell fate in animal caps, this procedure could be used to identify gene product(s) involved in specifying other tissues as well.

Tissue Determination Using the Animal Cap Transplant (ACT) Assay in <em>Xenopus laevis</em>

Many proteins play a dual role in embryonic development. Those that regulate cell fate determination in a specific tissue can also affect the development of a larger region of the embryo. This makes defining its role in a particular tissue difficult to analyze. For example, noggin overexpression in Xenopus laevis embryos causes the expansion of the entire anterior region, including the eye(1,2). From this result, it is not known if Noggin plays a direct role in eye determination or that by causing an expansion of neural tissue, Noggin indirectly affects eye formation. Having this complex phenotype makes studying its eye-specific role in cell fate determination difficult to analyze. We have developed an assay that overcomes this problem. Taking advantage of the pluripotent nature of the Xenopus laevis animal cap (3), we have developed an assay to test the ability of gene product(s), like noggin or the eye field transcription factors (EFTFs), to transform caps into particular tissue or cell types by transplanting this tissue onto the side of the embryo (4). While we have found either Noggin protein treatment or a collection of transcription factors can determine retinal cell fate in animal caps, this procedure could be used to identify gene product(s) involved in specifying other tissues as well.

TREMOR—a tool for retrieving transcriptional modules by incorporating motif covariance

A transcriptional module (TM) is a collection of transcription factors (TF) that as a group, co-regulate multiple, functionally related genes. The task of identifying TMs poses an important biological challenge. Since TFs belong to evolutionarily and structurally related families, TF family members often bind to similar DNA motifs and can confound sequence-based approaches to TM identification. A previous approach to TM detection addresses this issue by pre-selecting a single representative from each TF family. One problem with this approach is that closely related transcription factors can still target sufficiently distinct genes in a biologically meaningful way, and thus, pre-selecting a single family representative may in principle miss certain TMs. Here we report a method—TREMOR (Transcriptional Regulatory Module Retriever). This method uses the Mahalanobis distance to assess the validity of a TM and automatically incorporates the inter-TF binding similarity without resorting to pre-selecting family representatives. The application of TREMOR on human muscle-specific, liver-specific and cell-cycle-related genes reveals TFs and TMs that were validated from literature and also reveals additional related genes.