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Adenosine-to-inosine conversion at position 34 (A34-to-I) of certain tRNAs is essential for expanding their decoding capacity. This reaction is catalyzed by the adenosine deaminase acting on tRNA (ADAT) complex, which in Eukarya is formed by two subunits: ADAT2 and ADAT3. We herein identified and thoroughly characterized the ADAT molecules from the protozoan pathogen Trypanosoma cruzi, the causative agent of Chagas Disease. TcADAT2 and TcADAT3 spontaneously form a catalytically active complex, as shown by expression in engineered bacteria and/or by the increased ex vivo tRNA A-to-I deamination activity of T. cruzi epimastigotes overexpressing TcADAT subunits. Importantly, enhanced TcADAT2/3 activity in transgenic parasites caused a shift in their in vivo tRNAThrAGU signature, which correlated with significant changes in the expression of the Thr-rich TcSMUG proteins. To our knowledge, this is the first evidence indicating that T. cruzi tRNA editing can be modulated in vivo, in turn post-transcriptionally changing the expression of specific genes. Our findings suggest tRNA editing/availability as a forcible step in controlling gene expression and driving codon adaptation in T. cruzi. Moreover, we unveil certain differences between parasite and mammalian host tRNA editing and processing, such as cytosine-to-uridine conversion at position 32 of tRNAThrAGU in T. cruzi, that may be exploited for the identification of novel druggable targets of intervention.

CD4

microRNAs are short noncoding RNAs that regulate protein expression posttranscriptionally. We previously showed that miR-155 promotes effector CD8+ T-cell responses. However, little is known about the regulation of miR-155 expression. Here, we report that antigen affinity and dose determine miR-155 expression in CD8+ T cells. In B16 tumors expressing a low-affinity antigen ligand, tumor-specific infiltrating CD8+ T cells showed variable miR-155 expression, whereby high miR-155 expression was associated with more cytokine-producing cells and tumor control. Moreover, anti–PD-1 treatment led to both increased miR-155 expression and tumor control by specific CD8+ T cells. In addition, miR-155 overexpression enhanced exhausted CD8+ T-cell persistence in the LCMV cl13 chronic viral infection model. In agreement with these observations in mouse models, miR-155 expression in human effector memory CD8+ T cells positively correlated with their frequencies in tumor-infiltrated lymph nodes of melanoma patients. Low miR-155 target gene signature in tumors was associated with prolonged overall survival in melanoma patients. Altogether, these results raise the possibility that high miR-155 expression in CD8+ tumor-infiltrating T cells may be a surrogate marker of the relative potency of in situ antigen-specific CD8+ T-cell responses.

Single-cell RNA sequencing (scRNA-seq) has revealed an unprecedented degree of immune cell diversity. However, consistent definition of cell subtypes and cell states across studies and diseases remains a major challenge. Here we generate reference T cell atlases for cancer and viral infection by multi-study integration, and develop ProjecTILs, an algorithm for reference atlas projection. In contrast to other methods, ProjecTILs allows not only accurate embedding of new scRNA-seq data into a reference without altering its structure, but also characterizing previously unknown cell states that “deviate” from the reference. ProjecTILs accurately predicts the effects of cell perturbations and identifies gene programs that are altered in different conditions and tissues. A meta-analysis of tumor-infiltrating T cells from several cohorts reveals a strong conservation of T cell subtypes between human and mouse, providing a consistent basis to describe T cell heterogeneity across studies, diseases, and species., One challenge of single cell RNA sequencing analysis is how to consistently identify cell subtypes and states across different datasets. Here the authors propose the use of a reference single-cell atlas as a stable system of coordinates to characterize T cell states across studies, diseases and species.

Developing strategies to inflame tumors is critical for increasing response to immunotherapy. Here, we report that low-dose radiotherapy (LDRT) of murine tumors promotes T-cell infiltration and enables responsiveness to combinatorial immunotherapy in an IFN-dependent manner. Treatment efficacy relied upon mobilizing both adaptive and innate immunity and depended on both cytotoxic CD4+ and CD8+ T cells. LDRT elicited predominantly CD4+ cells with features of exhausted effector cytotoxic cells, with a subset expressing NKG2D and exhibiting proliferative capacity, as well as a unique subset of activated dendritic cells expressing the NKG2D ligand RAE1. We translated these findings to a phase I clinical trial administering LDRT, low-dose cyclophosphamide, and immune checkpoint blockade to patients with immune-desert tumors. In responsive patients, the combinatorial treatment triggered T-cell infiltration, predominantly of CD4+ cells with Th1 signatures. Our data support the rational combination of LDRT with immunotherapy for effectively treating low T cell–infiltrated tumors.Significance:Low-dose radiation reprogrammed the tumor microenvironment of tumors with scarce immune infiltration and together with immunotherapy induced simultaneous mobilization of innate and adaptive immunity, predominantly CD4+ effector T cells, to achieve tumor control dependent on NKG2D. The combination induced important responses in patients with metastatic immune-cold tumors.This article is highlighted in the In This Issue feature, p. 1

Recent studies have proposed that tumor-specific tumor-infiltrating CD8+ T lymphocytes (CD8 TIL) can be classified into two main groups: “exhausted” TILs, characterized by high expression of the inhibitory receptors PD-1 and TIM-3 and lack of transcription factor 1 (Tcf1); and “memory-like” TILs, with self-renewal capacity and co-expressing Tcf1 and PD-1. However, a comprehensive definition of the heterogeneity existing within both tumor-specific and total CD8 TILs has yet to be clearly established.To investigate this heterogeneity at the transcriptomic level, we performed paired single-cell RNA and TCR sequencing of CD8 T cells infiltrating B16 murine melanoma tumors, including cells of known tumor specificity. Unsupervised clustering and gene signature analysis revealed four distinct CD8 TIL states - exhausted, memory-like, naïve and effector memory-like (EM-like) - and predicted novel markers, including Ly6C for the EM-like cells, that were validated by flow cytometry. Tumor-specific PMEL T cells were predominantly found within the exhausted and memory-like states but also within the EM-like state. Further, TCR repertoire sequencing revealed a large clonal expansion of exhausted, memory-like and EM-like cells with partial clonal relatedness between them. Finally, meta-analyses of public bulk and single-cell RNA-seq data suggested that anti-PD-1 treatment induces expansion of EM-like cells.Our reference map of the transcriptomic landscape of murine CD8 TILs will help interpreting future bulk and single-cell transcriptomic studies and may guide the analysis of CD8 TIL subpopulations in response to therapeutic interventions.

Checkpoint blockade mediates a proliferative response of tumor-infiltrating CD8

Baculoviruses are large DNA virus of insects principally employed in recombinant protein expression. Its ability to form occlusion bodies (OBs), which are composed mainly of polyhedrin protein (POLH), makes them biotechnologically attractive, as these crystals (polyhedra) can incorporate foreign peptides and can be easily isolated. On the other hand, peptide microarrays allow rapid and inexpensive high-throughput serological screening of new candidates to be incorporated to OBs. To integrate these 2 biotechnological approaches, we worked on Babesia bovis, one of the causative agents of bovine babesiosis. Current molecular diagnosis of infection with B. bovis includes enzyme-linked immunosorbent assay (ELISA) techniques, which use merozoite lysate obtained from infected bovine erythrocytes. However, it is important to produce recombinant antigens that replace the use of crude antigens. Here, we describe a new biotechnological platform for the design of indirect ELISAs based on 5 antigenic peptides of 15 amino acid residues of B. bovis (ApBb), selected from a peptide microarray and expressed as a fusion to POLH. An Sf9POLHE44G packaging cell line infected with recombinant baculoviruses carrying POLH-ApBb fusions yielded higher levels of chimeric polyhedra, highlighting the advantage of a trans-contribution of a mutant copy of polyhedrin. Finally, the use of dissolved recombinant polyhedra as antigens was successful in an ELISA assay, as B. bovis-positive sera recognized the fusion POLH-ApBb. Thus, the use of this platform resulted in a promising alternative for molecular diagnosis of relevant infectious diseases. Fil: López, María Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina Fil: Pallarés, Horacio Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina Fil: Alfonso, Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina Fil: Carmona, S. J.. Universite de Lausanne; Suiza. Swiss Institute of Bioinformatics; Suiza Fil: Farber, Marisa Diana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Taboga, Oscar Alberto. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Wilkowsky, Silvina Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina

The immune system of vertebrate species consists of many different cell types that have distinct functional roles and are subject to different evolutionary pressures. Here, we first analyzed conservation of genes specific for all major immune cell types in human and mouse. Our results revealed higher gene turnover and faster evolution of trans-membrane proteins in NK cells compared with other immune cell types, and especially T cells, but similar conservation of nuclear and cytoplasmic protein coding genes. To validate these findings in a distant vertebrate species, we used single-cell RNA sequencing of lck:GFP cells in zebrafish and obtained the first transcriptome of specific immune cell types in a nonmammalian species. Unsupervised clustering and single-cell TCR locus reconstruction identified three cell populations, T cells, a novel type of NK-like cells, and a smaller population of myeloid-like cells. Differential expression analysis uncovered new immune-cell–specific genes, including novel immunoglobulin-like receptors, and neofunctionalization of recently duplicated paralogs. Evolutionary analyses confirmed the higher gene turnover of trans-membrane proteins in NK cells compared with T cells in fish species, suggesting that this is a general property of immune cell types across all vertebrates.

Innate lymphoid cells (ILCs) consist of natural killer (NK) cells and non-cytotoxic ILCs that are broadly classified into ILC1, ILC2, and ILC3 subtypes. These cells recently emerged as important early effectors of innate immunity for their roles in tissue homeostasis and inflammation. Over the last few years, ILCs have been extensively studied in mouse and human at the functional and molecular level, including gene expression profiling. However, sorting ILCs with flow cytometry for gene expression analysis is a delicate and time-consuming process. Here we propose and validate a novel framework for studying ILCs at the transcriptomic level using single-cell RNA-Seq data. Our approach combines unsupervised clustering and a new cell type classifier trained on mouse ILC gene expression data. We show that this approach can accurately identify different ILCs, especially ILC2 cells, in human lymphocyte single-cell RNA-Seq data. Our new model relies only on genes conserved across vertebrates, thereby making it in principle applicable in any vertebrate species. Considering the rapid increase in throughput of single-cell RNA-Seq technology, our work provides a computational framework for studying ILC2 cells in single-cell transcriptomic data and may help exploring their conservation in distant vertebrate species.

Checkpoint blockade mediates a proliferative response of tumor-infiltrating CD8 + T lymphocytes (TILs). The origin of this response has remained elusive because chronic activation promotes terminal differentiation or exhaustion of tumor-specific T cells. Here we identified a subset of tumor-reactive TILs bearing hallmarks of exhausted cells and central memory cells, including expression of the checkpoint protein PD-1 and the transcription factor Tcf1. Tcf1 + PD-1 + TILs mediated the proliferative response to immunotherapy, generating both Tcf1 + PD-1 + and differentiated Tcf1 - PD-1 + cells. Ablation of Tcf1 + PD-1 + TILs restricted responses to immunotherapy. Tcf1 was not required for the generation of Tcf1 + PD-1 + TILs but was essential for the stem-like functions of these cells. Human TCF1 + PD-1 + cells were detected among tumor-reactive CD8 + T cells in the blood of melanoma patients and among TILs of primary melanomas. Thus, immune checkpoint blockade relies not on reversal of T cell exhaustion programs, but on the proliferation of a stem-like TIL subset.

The TcSNP database (http://snps.tcruzi.org) integrates information on genetic variation (polymorphisms and mutations) for different stocks, strains and isolates of Trypanosoma cruzi, the causative agent of Chagas disease. The database incorporates sequences (genes from the T. cruzi reference genome, mRNAs, ESTs and genomic sequences); multiple sequence alignments obtained from these sequences; and single-nucleotide polymorphisms and small indels identified by scanning these multiple sequence alignments. Information in TcSNP can be readily interrogated to arrive at gene sets, or SNP sets of interest based on a number of attributes. Sequence similarity searches using BLAST are also supported. This first release of TcSNP contains nearly 170 000 high-confidence candidate SNPs, derived from the analysis of annotated coding sequences. As new sequence data become available, TcSNP will incorporate these data, mapping new candidate SNPs onto the reference genome sequences.

The availability of complete pathogen genomes has renewed interest in the development of diagnostics for infectious diseases. Synthetic peptide microarrays provide a rapid, high-throughput platform for immunological testing of potential B-cell epitopes. However, their current capacity prevent the experimental screening of complete "peptidomes". Therefore, computational approaches for prediction and/or prioritization of diagnostically relevant peptides are required. In this work we describe a computational method to assess a defined set of molecular properties for each potential diagnostic target in a reference genome. Properties such as sub-cellular localization or expression level were evaluated for the whole protein. At a higher resolution (short peptides), we assessed a set of local properties, such as repetitive motifs, disorder (structured vs natively unstructured regions), trans-membrane spans, genetic polymorphisms (conserved vs. divergent regions), predicted B-cell epitopes, and sequence similarity against human proteins and other potential cross-reacting species (e.g. other pathogens endemic in overlapping geographical locations). A scoring function based on these different features was developed, and used to rank all peptides from a large eukaryotic pathogen proteome. We applied this method to the identification of candidate diagnostic peptides in the protozoan Trypanosoma cruzi, the causative agent of Chagas disease. We measured the performance of the method by analyzing the enrichment of validated antigens in the high-scoring top of the ranking. Based on this measure, our integrative method outperformed alternative prioritizations based on individual properties (such as B-cell epitope predictors alone). Using this method we ranked [Formula: see text]10 million 12-mer overlapping peptides derived from the complete T. cruzi proteome. Experimental screening of 190 high-scoring peptides allowed the identification of 37 novel epitopes with diagnostic potential, while none of the low scoring peptides showed significant reactivity. Many of the metrics employed are dependent on standard bioinformatic tools and data, so the method can be easily extended to other pathogen genomes.

Background The increased sequencing of pathogen genomes and the subsequent availability of genome-scale functional datasets are expected to guide the experimental work necessary for target-based drug discovery. However, a major bottleneck in this has been the difficulty of capturing and integrating relevant information in an easily accessible format for identifying and prioritizing potential targets. The open-access resource TDRtargets.org facilitates drug target prioritization for major tropical disease pathogens such as the mycobacteria Mycobacterium leprae and Mycobacterium tuberculosis; the kinetoplastid protozoans Leishmania major, Trypanosoma brucei, and Trypanosoma cruzi; the apicomplexan protozoans Plasmodium falciparum, Plasmodium vivax, and Toxoplasma gondii; and the helminths Brugia malayi and Schistosoma mansoni. Methodology/Principal Findings Here we present strategies to prioritize pathogen proteins based on whether their properties meet criteria considered desirable in a drug target. These criteria are based upon both sequence-derived information (e.g., molecular mass) and functional data on expression, essentiality, phenotypes, metabolic pathways, assayability, and druggability. This approach also highlights the fact that data for many relevant criteria are lacking in less-studied pathogens (e.g., helminths), and we demonstrate how this can be partially overcome by mapping data from homologous genes in well-studied organisms. We also show how individual users can easily upload external datasets and integrate them with existing data in TDRtargets.org to generate highly customized ranked lists of potential targets. Conclusions/Significance Using the datasets and the tools available in TDRtargets.org, we have generated illustrative lists of potential drug targets in seven tropical disease pathogens. While these lists are broadly consistent with the research community's current interest in certain specific proteins, and suggest novel target candidates that may merit further study, the lists can easily be modified in a user-specific manner, either by adjusting the weights for chosen criteria or by changing the criteria that are included., Author Summary In cell-based drug development, researchers attempt to create drugs that kill a pathogen without necessarily understanding the details of how the drugs work. In contrast, target-based drug development entails the search for compounds that act on a specific intracellular target—often a protein known or suspected to be required for survival of the pathogen. The latter approach to drug development has been facilitated greatly by the sequencing of many pathogen genomes and the incorporation of genome data into user-friendly databases. The present paper shows how the database TDRtargets.org can identify proteins that might be considered good drug targets for diseases such as African sleeping sickness, Chagas disease, parasitic worm infections, tuberculosis, and malaria. These proteins may score highly in searches of the database because they are dissimilar to human proteins, are structurally similar to other “druggable” proteins, have functions that are easy to measure, and/or fulfill other criteria. Researchers can use the lists of high-scoring proteins as a basis for deciding which potential drug targets to pursue experimentally.

In the context of adoptive T cell transfer (ACT) for cancer treatment, it is crucial to generate in vitro large amounts of tumor-specific CD8 T cells with high potential to persist in vivo. PD-1, Tim3, and CD39 have been proposed as markers of tumor-specific tumor-infiltrating CD8 T lymphocytes (CD8 TILs). However, these molecules are highly expressed by terminally differentiated exhausted CD8 T cells (Tex) that lack proliferation potential. Therefore, optimized strategies to isolate tumor-specific TILs with high proliferative potential, such as Tcf1+ precursor exhausted T cells (Tpe) are needed to improve in vivo persistence of ACT. Here we aimed at defining cell surface markers that would unequivocally identify Types for precision cell sorting increasing the purity of tumor-specific PD-1+ Tcf1+ Tpe from total TILs. Transcriptomic analysis of Tpe vs. Tex CD8 TIL subsets from B16 tumors and primary human melanoma tumors revealed that Tpes are enriched in Slamf6 and lack Entpd1 and Havcr2 expression, which encode Slamf6, CD39, and Tim3 cell surface proteins, respectively. Indeed, we observed by flow cytometry that CD39– Tim3– Slamf6+ PD-1+ cells yielded maximum enrichment for tumor specific PD-1+ Tcf1+ OT1 TILs in B16.OVA tumors. Moreover, this population showed higher re-expansion capacity upon an acute infection recall response compared to the CD39+ counterparts or bulk PD-1+ TILs. Hence, we report an enhanced sorting strategy (CD39– Tim3– Slamf6+ PD-1+) of Tpes. In conclusion, we show that optimization of CD8 TIL cell sorting strategy is a viable approach to improve recall capacity and in vivo persistence of transferred cells in the context of ACT.