Systemwide in vivo , multi-omics and computational approaches to understand tumor immune coevolution and RNA secretion

Tumor progression is the major cause of death in cancer patients. Due to their higher chromosomal instability and other genomic alterations, tumors evolve rapidly in response to therapeutic interventions and other external pressures. The immune system is our first line of defense against cancer and its interaction with cancer cells can both constrain and promote tumor growth and metastasis. A heterogeneous tumor consists of subclones with different characteristics. During tumor progression the anti-tumor immune activity removes subclones that express highly immunogenic antigens and leaves behind cancer cells with high immune escape or immunosuppressive properties. This process is called tumor immunoediting. Studying tumor progression requires reliable in vivo models that effectively capture the intricacies and complexities of this process. During the 1970s, Isaiah Fidler demonstrated that repeated passaging of cancer cells in mice can be used to emulate metastatic progression. This in vivo selection model has been used by many different research groups (including us) to model tumor progression in a number of cancer models. Our group has utilized these in vivo selection models to study cell autonomous mechanisms of tumor progression. More recently, however, we have come to realize that by leveraging these in vivo-selection models we can focus on studying non-cell autonomous mechanisms. Building on this notion, here, we propose a generalization of in vivo selection that models the role of the immune system in shaping tumor evolution. Our “immune selection” model takes advantage of a panel of genetic mouse models with various degrees of immunocompetency to serve as hosts for established syngeneic tumor cell lines. We utilized these ‘immuno-selected’ derivatives, in conjunction with cutting-edge tools in genetic engineering and single-cell genomics, to study the tumor-immune co-evolution. We discovered that the interferon response pathway lies at the heart of tumor immune evasion. Additionally, we have uncovered novel molecular pathways responsible for conferring resistance to both antitumor immunity and immunotherapies. Targeting these pathways holds significant therapeutic potential, particularly when used in conjunction with immune checkpoint blockades (ICBs) and other forms of immunotherapy. The second part of this thesis is focused on utilizing machine learning and computational tools to identify important molecular mechanisms in small RNA secretion. We developed ExoGRU, a deep-learning model for predicting secretion probabilities of small RNAs based on their primary sequence. We used ExoGRU to (i) identify mutations that abrogate the secretion of known cell-free small RNAs, and (ii) predict high confidence sets of synthetic sequences that are secreted or retained. We also used independent experimental approaches to validate our model’s prediction abilities. We discovered that the molecular signature needed for small RNA secretion lies in its primary sequence. Furthermore, we identified both previously known and novel RNA binding proteins (RBPs) crucial for facilitating this secretion. In both projects discussed, we demonstrate the effectiveness of in vivo, high-throughput, multi-omics and computational tools in uncovering novel mechanisms, particularly in the evolution of tumor immunity and RNA secretion, areas traditionally challenging to explore with conventional methods

Characterization of phytoplasmas related to aster yellows group infecting annual plants in Iran, based on the studies of 16S rRNA and rp genes

Several annual field crops, vegetables, ornamentals, oilseed crops, and weeds showing phytoplasma diseases symptoms were collected to detect phytoplasmas related to ‘Candidatus Phytoplasma asteris’. The collecting was done in the central regions of Iran. For general detection of phytoplasmas, 16S rRNA gene fragments were amplified using phytoplasma universal primer pair P1/P7 in polymerase chain reaction (PCR) followed by primer pair R16F2n/R16R2 in nested PCR. Then, for finer detection of phytoplasmas related to ‘Ca. P. asteris’, DNA samples were used to extend the rp and tuf gene fragments by PCR using aster yellows group specific primer pairs rp(I)F1A/rp(I)R1A and fTufAy/rTufAy, respectively. Restriction fragment lenght polymorphism (RFLP) analysis of rp gene fragments using digestion with AluI, MseI, and Tsp509I restriction enzymes indicated that aster yellows group related phytoplasmas in these Iranian regions, belong to rpI-B subgroups. Sequence analysis of partial 16S rRNA and rp genes from representative phytoplasma isolates confirmed the RFLP results. This research is the first report of annual plants infected with phytoplasmas related to subgroup rpI-B in Iran

Characterization of phytoplasmas related to 'Candidatus Phytoplasma asteris' subgroup rpI-L in Iran

In two of Iran's central provinces, several herbaceous plants showing phytoplasma disease symptoms were collected to detect 'Canididatus Phytoplasma asteris'-related phytoplasmas. Confirmation of an association of phytoplasmas with diseased plants was done using polymerase chain reaction (PCR) assays having the phytoplasma universal primer pairs P1/P7 followed by R16F2n/ R16R2 in nested PCR. Then, for detection of 'Ca. P. asteris', DNA samples were subjected to amplification of rp and tuf genes using specific primer pairs rp(I)F1A/rp(I)R1A and fTufAy/rTufAy, respectively. Restriction fragment length polymorphism or RFLP analyses of rp gene fragments using Tsp509I restriction enzyme as well as sequence analyses indicated that 'Ca. P. asteris'-related phytoplasmas associated with carrot, niger seed and scallion plants in these regions, belong to the rpI-L subgroup. This research is the first report of carrot, niger seed, and scallion infection with phytoplasmas belonging to the rpI-L subgroup

Characterization of phytoplasmas related to ‘Candidatus Phytoplasma asteris’ subgroup rpI-L in Iran

In two of Iran's central provinces, several herbaceous plants showing phytoplasma disease symptoms were collected to detect 'Canididatus Phytoplasma asteris'-related phytoplasmas. Confirmation of an association of phytoplasmas with diseased plants was done using polymerase chain reaction (PCR) assays having the phytoplasma universal primer pairs P1/P7 followed by R16F2n/ R16R2 in nested PCR. Then, for detection of 'Ca. P. asteris', DNA samples were subjected to amplification of rp and tuf genes using specific primer pairs rp(I)F1A/rp(I)R1A and fTufAy/rTufAy, respectively. Restriction fragment length polymorphism or RFLP analyses of rp gene fragments using Tsp509I restriction enzyme as well as sequence analyses indicated that 'Ca. P. asteris'-related phytoplasmas associated with carrot, niger seed and scallion plants in these regions, belong to the rpI-L subgroup. This research is the first report of carrot, niger seed, and scallion infection with phytoplasmas belonging to the rpI-L subgroup

Fas ligand promotes an inducible TLR-dependent model of cutaneous lupus-like inflammation

Toll-like receptors TLR7 and TLR9 are both implicated in the activation of autoreactive B cells and other cell types associated with systemic lupus erythematosus (SLE) pathogenesis. However, Tlr9-/- autoimmune-prone strains paradoxically develop more severe disease. We have now leveraged the negative regulatory role of TLR9 to develop an inducible rapid-onset murine model of systemic autoimmunity that depends on T cell detection of a membrane-bound OVA fusion protein expressed by MHC class II+ cells, expression of TLR7, expression of the type I IFN receptor, and loss of expression of TLR9. These mice are distinguished by a high frequency of OVA-specific Tbet+, IFN-gamma+, and FasL-expressing Th1 cells as well as autoantibody-producing B cells. Unexpectedly, contrary to what occurs in most models of SLE, they also developed skin lesions that are very similar to those of human cutaneous lupus erythematosus (CLE) as far as clinical appearance, histological changes, and gene expression. FasL was a key effector mechanism in the skin, as the transfer of FasL-deficient DO11gld T cells completely failed to elicit overt skin lesions. FasL was also upregulated in human CLE biopsies. Overall, our model provides a relevant system for exploring the pathophysiology of CLE as well as the negative regulatory role of TLR9

Revealing the grammar of small RNA secretion using interpretable machine learning.

Small non-coding RNAs can be secreted through a variety of mechanisms, including exosomal sorting, in small extracellular vesicles, and within lipoprotein complexes. However, the mechanisms that govern their sorting and secretion are not well understood. Here, we present ExoGRU, a machine learning model that predicts small RNA secretion probabilities from primary RNA sequences. We experimentally validated the performance of this model through ExoGRU-guided mutagenesis and synthetic RNA sequence analysis. Additionally, we used ExoGRU to reveal cis and trans factors that underlie small RNA secretion, including known and novel RNA-binding proteins (RBPs), e.g., YBX1, HNRNPA2B1, and RBM24. We also developed a novel technique called exoCLIP, which reveals the RNA interactome of RBPs within the cell-free space. Together, our results demonstrate the power of machine learning in revealing novel biological mechanisms. In addition to providing deeper insight into small RNA secretion, this knowledge can be leveraged in therapeutic and synthetic biology applications

Treg-Cell Control of a CXCL5-IL-17 Inflammatory Axis Promotes Hair-Follicle-Stem-Cell Differentiation During Skin-Barrier Repair.

Restoration of barrier-tissue integrity after injury is dependent on the function of immune cells and stem cells (SCs) residing in the tissue. In response to skin injury, hair-follicle stem cells (HFSCs), normally poised for hair generation, are recruited to the site of injury and differentiate into cells that repair damaged epithelium. We used a SC fate-mapping approach to examine the contribution of regulatory T (Treg) cells to epidermal-barrier repair after injury. Depletion of Treg cells impaired skin-barrier regeneration and was associated with a Th17 inflammatory response and failed HFSC differentiation. In this setting, damaged epithelial cells preferentially expressed the neutrophil chemoattractant CXCL5, and blockade of CXCL5 or neutrophil depletion restored barrier function and SC differentiation after epidermal injury. Thus, Treg-cell regulation of localized inflammation enables HFSC differentiation and, thereby, skin-barrier regeneration, with implications for the maintenance and repair of other barrier tissues

Regulatory T Cells in Skin Facilitate Epithelial Stem Cell Differentiation

The maintenance of tissue homeostasis is critically dependent on the function of tissue-resident immune cells and the differentiation capacity of tissue-resident stem cells (SCs). How immune cells influence the function of SCs is largely unknown. Regulatory T cells (Tregs) in skin preferentially localize to hair follicles (HFs), which house a major subset of skin SCs (HFSCs). Here, we mechanistically dissect the role of Tregs in HF and HFSC biology. Lineage-specific cell depletion revealed that Tregs promote HF regeneration by augmenting HFSC proliferation and differentiation. Transcriptional and phenotypic profiling of Tregs and HFSCs revealed that skin-resident Tregs preferentially express high levels of the Notch ligand family member, Jagged 1 (Jag1). Expression of Jag1 on Tregs facilitated HFSC function and efficient HF regeneration. Taken together, our work demonstrates that Tregs in skin play a major role in HF biology by promoting the function of HFSCs. [Display omitted] •Treg activation in skin closely correlates with the HF cycle•Tregs localize to HFSCs and play a major role in HF regeneration•Tregs facilitate HFSC proliferation and differentiation to initiate HF cycling•Treg expression of Jagged 1 is required for efficient hair regeneration Localized regulatory T cells (Tregs) regulate the hair follicle cycle by driving Notch-dependent stem cell proliferation and differentiation