Biology subjects
Publications and source records attributed to Jones, R..
A rare coding variant of Abelson-interactor gene family member 3 (Abi3) is associated with increased risk of late-onset Alzheimers Disease (AD). Although Abi3 is recognised as a core microglial gene, its role in microglia is largely unknown. Here we demonstrate that Abi3 is crucial for normal microglial morphology, distribution, and homeostatic tissue surveillance activity in vivo.
Individualized neoantigen specific immunotherapy (iNeST) requires robustly expressed clonal neoantigens for efficacy, but tumor mutational heterogeneity, loss of neoantigen expression, and variable tissue sampling present challenges. To characterize these potential obstacles, we combined multi-region sequencing (MR-seq) analysis of five untreated, synchronously sampled metastatic solid tumors with re-analysis of published MR-seq data from 103 patients. Branching evolution in colorectal cancer and renal cell carcinoma led to fewer clonal neoantigens and to clade-specific neoantigens (those shared across a subset of tumor regions but not fully clonal), with the latter not being readily distinguishable in single tumor samples. Prioritizing mutations with higher purity- and ploidy-adjusted variant allele frequency enriched for globally clonal neoantigens (those found in all tumor regions), whereas estimated cancer cell fraction derived from clustering-based tools, surprisingly, did not. Neoantigen quality was associated with loss of neoantigen expression in the bladder cancer case, and HLA-allele loss was observed in the renal and non-small cell lung cancer cases. Our results show that indication type, multi-lesion sampling, neoantigen expression, and HLA allele retention are important factors for iNeST targeting and patient selection.
While many useful microstructural indices, as well as orientation distribution functions, can be obtained from multi-shell dMRI data, there is growing interest in exploring the richer set of microstructural features that can be extracted from the full ensemble average propagator (EAP). The EAP can be readily computed from diffusion spectrum imaging (DSI) data, at the cost of a very lengthy acquisition. Compressed sensing (CS) has been used to make DSI more practical by reducing its acquisition time. CS applied to DSI (CS-DSI) attempts to reconstruct the EAP from significantly undersampled q-space data. We present a post mortem validation study where we evaluate the ability of CS-DSI to approximate not only fully sampled DSI but also multi-shell acquisitions with high fidelity. Human brain samples are imaged with high-resolution DSI at 9.4T and with polarization-sensitive optical coherence tomography (PSOCT). The latter provides direct measurements of axonal orientations at microscopic resolutions, allowing us to evaluate the mesoscopic orientation estimates obtained from diffusion MRI, in terms of their angular error and the presence of spurious peaks. We test two fast, dictionary-based, L2-regularized algorithms for CS-DSI reconstruction. We find that, for a CS acceleration factor of R=3, i.e., an acquisition with 171 gradient directions, one of these methods is able to achieve both low angular error and low number of spurious peaks. With a scan length similar to that of high angular resolution multi-shell acquisition schemes, this CS-DSI approach is able to approximate both fully sampled DSI and multi-shell data with high accuracy. Thus it is suitable for orientation reconstruction and microstructural modeling techniques that require either grid- or shell-based acquisitions. We find that the signal-to-noise ratio (SNR) of the training data used to construct the dictionary can have an impact on the accuracy of CS-DSI, but that there is substantial robustness to loss of SNR in the test data. Finally, we show that, as the CS acceleration factor increases beyond R=3, the accuracy of these reconstruction methods degrade, either in terms of the angular error, or in terms of the number of spurious peaks. Our results provide useful benchmarks for the future development of even more efficient q-space acceleration techniques.
For over a decade, multiple studies have disputed the notion of natural killer (NK) cells as purely innate lymphocytes by demonstrating that they are capable of putative antigen-specific immunological memory against multiple infectious agents including two critical global health priorities - HIV and influenza. However, the mechanisms underlying antigen specificity remain unknown. Herein, we demonstrate that antigen-specific human NK cell memory develops upon exposure to both HIV and influenza, unified by a conserved and epitope-specific targetable mechanism firmly dependent on the activating CD94/NKG2C receptor and its ligand HLA-E, and confirm these findings by three rigorous and novel assays. We validated the permanent acquisition of antigen-specificity by individual memory NK cells by single-cell cloning. We identified biomarkers of antigen-specific NK cell memory through RNA-Seq transcriptomic fingerprints and complex immunophenotyping by 30-parameter flow cytometry showing elevated expression of KLRG1, 4{beta}7 and NKG2C. Finally, we show individual HLA-E-restricted peptides that may constitute the dominant response in HIV-1- and influenza-infected persons in vivo. Our findings clarify the mechanisms behind formation of antigen-specific memory NK cells, and suggest they could be targeted for future vaccines, cure strategies, or other therapeutic interventions.
Cerebral organoids provide unparalleled access to human brain development in vitro. However, variability induced by current culture methodologies precludes using organoids as robust disease models. To address this, we developed an automated Organoid Culture and Assay (ORCA) system to support longitudinal unbiased phenotyping of organoids at scale across multiple patient lines. We then characterized organoid variability using novel machine learning methods and found that the contribution of donor, clone, and batch is significant and remarkably consistent over gene expression, morphology, and cell-type composition. Next, we performed multi-factorial protocol optimization, producing a directed forebrain protocol compatible with 96-well culture that exhibits low variability while preserving tissue complexity. Finally, we used ORCA to study tuberous sclerosis, a disease with known genetics but poorly representative animal models. For the first time, we report highly reproducible early morphological and molecular signatures of disease in heterozygous TSC+/- forebrain organoids, demonstrating the benefit of a scaled organoid system for phenotype discovery in human disease models.
DNA methyl-transferase-1 or DNMT1 maintains DNA methylation in the genome and is important for regulating gene expression in cells. Aberrant changes in DNMT1 activity are observed in many diseases. Therefore, understanding the mechanisms behind alteration of DNMT1 activity is important. Here, we show that CCDC26, a nuclear long non-coding RNA frequently mutated in myeloid leukaemia, directly interacts with DNMT1. In the absence of CCDC26 RNA, DNMT1 is mis-located in the cytoplasm. As a result, genomic DNA is significantly hypomethylated, which is accompanied by a slower cell growth rate and increased cell death. These results point to a previously unrecognised mechanism of long non-coding RNA mediated subcellular localisation of DNMT1 and regulation of DNA methylation. These observations are significant given the importance of DNMT1 in cancer and number of other diseases.
BackgroundThree arthorpod-borne viruses (arboviruses) causing human disease have been the focus of a large number of studies in the Americas since 2013 due to their global spread and epidemiological impacts: Zika, dengue, and chikungunya viruses. A large proportion of infections by these viruses are asymptomatic. However, all three viruses are associated with moderate to severe health consequences in a small proportion of cases. Two mosquito species, Aedes aegypti and Aedes albopictus, are among the worlds most prominent arboviral vectors, and are known primary vectors for all three viruses in the Americas.\n\nObjectivesThis review summarizes the state of the entomological literature surrounding the biology and ecology of vectors of Zika, dengue and chikungunya viruses and factors affecting virus transmission. The rationale of the review was to elucidate consensus and discord between studies, and guide future research based on identified knowledge gaps.\n\nResultsA total of 196 studies were included in the scoping review after initial screening and subsequent exclusion of out-of-scope studies, secondary data publications, duplicate records, and studies unavailable in English language.\n\nKey findingsTemperature and humidity have the strongest impact on mosquito distribution and dynamics, development of immatures and arborviral infection rates. Low socioeconomic status and related factors, including poor infrastructure, inconsistent access to water, and high household resident density, have been consistently associated with arbovirus vector occurrence. Effects of interspecific competition on arboviral vector species is currently poorly understood. Vector competence for Zika virus is well established for Ae. aegypti and Ae. albopictus. Information on Zika virus vector transmission dynamics is sparse in contrast to the wealth of research available for dengue and chikungunya viruses.\n\nConclusionsBased on the internationally recognized urgency of Zika virus infection as a public health concern, further research on arbovirus vectors and transmission dynamics is of pressing need.
CAR T cells mediate antitumor effects in a small subset of cancer patients, but dysfunction due to T cell exhaustion is an important barrier to progress. To investigate the biology of exhaustion in human T cells expressing CAR receptors, we used a model system employing a tonically signaling CAR, which induces hallmarks of exhaustion described in other settings. Exhaustion was associated with a profound defect in IL-2 production alongside increased chromatin accessibility of AP-1 transcription factor motifs, and overexpression of numerous bZIP and IRF transcription factors that have been implicated in inhibitory activity. Here we demonstrate that engineering CAR T cells to overexpress c-Jun, a canonical AP-1 factor, enhanced expansion potential, increased functional capacity, diminished terminal differentiation and improved antitumor potency in numerous in vivo tumor models. We conclude that a functional deficiency in c-Jun mediates dysfunction in exhausted human T cells and that engineering CAR T cells to overexpress c-Jun renders them exhaustion-resistant, thereby addressing a major barrier to progress for this emerging class of therapeutics.
Breathing rate and depth influence the concentration of carbon dioxide in the blood, altering cerebral blood flow and thus functional magnetic resonance imaging (fMRI) signals. Such respiratory fluctuations can have substantial influence in studies of fMRI signal covariance in subjects at rest, the so-called \"resting state functional connectivity\" technique. If respiration is monitored during fMRI scanning, it is typically done using a belt about the subjects abdomen to record abdominal circumference. Several measures have been derived from these belt records, including the windowed envelope of the waveform (ENV), the windowed variance in the waveform (respiration variation, RV), and a measure of the amplitude of each breath divided by the cycle time of the breath (respiration volume per time, RVT). Any attempt to gauge respiratory contributions to fMRI signals requires a respiratory measure, but little is known about how these measures compare to each other, or how they perform beyond the small studies in which they were initially proposed. In this paper, we examine the properties of these measures in hundreds of healthy young adults scanned for an hour each at rest, a subset of the Human Connectome Project chosen for having high-quality physiological records. We find: 1) ENV, RV, and RVT are all similar, though ENV and RV are more similar to each other than to RVT; 2) respiratory events like deep breaths exhibit characteristic fMRI signal changes, head motions, and image quality abnormalities time-locked to deep breaths evident in the belt traces; 3) all measures can \"miss\" respiratory events evident in the belt traces; 4) RVT \"misses\" deep breaths (i.e., yawns and sighs) more than ENV or RV; 5) all respiratory measures change systematically over the course of a 14.4-minute scan, decreasing in mean value. We discuss the implication of these findings for the literature, and ways to move forward in modeling respiratory influences on fMRI scans.\n\nHighlights- Examines 3 respiratory measures in resting state fMRI scans of healthy young adults\n- All respiratory measures \"miss\" respiratory events, some more than others\n- Respiration volume per time (RVT) frequently \"misses\" deep breaths\n- All respiratory measures decrease systematically over 14.4 minute scans\n- Systematic decreases are due to decreased breathing depth and rate
Head motion estimates in functional magnetic resonance imaging (fMRI) scans appear qualitatively different with sub-second image sampling rates compared to the multi-second sampling rates common in the past. Whereas formerly the head appeared still for much of a scan with brief excursions from baseline, the head now appears to be in constant motion, and motion estimates often seem to divulge little information about what is happening in a scan. This constant motion has been attributed to respiratory oscillations that do not alias at faster sampling rates, and investigators are divided on the extent to which such motion is \"real\" motion or only \"apparent\" pseudomotion. Some investigators have abandoned the use of motion estimates entirely due to these considerations. Here we investigate the properties of motion in several fMRI datasets sampled at rates between 720-1160 ms, and describe 5 distinct kinds of respiratory motion: 1) constant real respiratory motion in the form of head nodding most evident in vertical position and pitch, which can be very large; 2) constant pseudomotion at the same respiratory rate as real motion, occurring only in the phase encode direction; 3) punctate real motions occurring at times of very deep breaths; 4) a low-frequency pseudomotion in only the phase encode direction following very deep breaths; 5) slow modulation of vertical and anterior-posterior head position by the respiratory envelope. We reformulate motion estimates in light of these considerations and obtain good concordance between motion estimates, physiologic records, image quality measures, and events evident in the fMRI signals.\n\nHighlights- Examines several fast-TR datasets with sampling rates of 720-1160 ms\n- Identifies 7 kinds of motion in fMRI scans, 5 of them related to respiration\n- Identifies 2 forms of pseudomotion occurring only in phase encode direction\n- Pseudomotion is a function of soft tissue mass, not lung volume\n- Reformulates motion estimates to draw out particular kinds of motion
Cohesin entraps sister DNAs within tripartite rings created by pairwise interactions between Smc1,Smc3, and Scc1. Because the ATPase heads of Smc1 and Smc3 can interact with each other, cohesin rings in fact have the potential to form a variety of sub-compartments. Using in vivo cysteine crosslinking,we show that when Smc1 and Smc3 ATPases are engaged in the presence of ATP (E heads)cohesin rings generate a \"SMC (S) compartment\" between hinge and E heads and a \"kleisin (K)compartment\" between E heads and their associated kleisin subunit. Upon ATP hydrolysis, cohesins heads associate with each other in a very different mode, in which their signature motifs and their coiled coils are closely juxtaposed (J heads), creating alternative S and K compartments. We show that all four sub-compartments exist in vivo, that acetylation of Smc3 during S phase is accompanied by an increase in the ratio of J to E heads, and that sister DNAs are entrapped in J-K but not E-K compartments or in either type of S compartment.
TFEB and TFE3 are transcriptional regulators of the innate immune response, but the mechanisms regulating their activation upon pathogen infection are poorly elucidated. Using C. elegans and mammalian models, we report that the master metabolic modulator 5-AMP-activated protein kinase (AMPK) and its negative regulator Folliculin (FLCN) act upstream of TFEB/TFE3 in the innate immune response, independently of the mTORC1 signaling pathway. In nematodes, loss of FLCN or overexpression of AMPK conferred pathogen resistance via activation of TFEB/TFE3-dependent antimicrobial genes, while ablation of total AMPK activity abolished this phenotype. Similarly, in mammalian cells, loss of FLCN or pharmacological activation of AMPK induced TFEB/TFE3-dependent pro-inflammatory cytokine expression. Importantly, a rapid reduction in cellular ATP levels in murine macrophages was observed upon lipopolysaccharide (LPS) treatment accompanied by an acute AMPK activation and TFEB nuclear localization. These results uncover an ancient, highly conserved and pharmacologically actionable mechanism coupling energy status with innate immunity.
Recently high-throughput image-based transcriptomic methods were developed and enabled researchers to spatially resolve gene expression variation at the molecular level for the first time. In this work, we develop a general analysis tool to quantitatively study the spatial correlations of gene expression in fixed tissue sections. As an illustration, we analyze the spatial distribution of single mRNA molecules measured by in situ sequencing on human fetal pancreas at three developmental time points 80, 87 and 117 days post-fertilization. We develop a density profile-based method to capture the spatial relationship between gene expression and other morphological features of the tissue sample such as position of nuclei and endocrine cells of the pancreas. In addition, we build a statistical model to characterize correlations in the spatial distribution of the expression level among different genes. This model enables us to infer the inhibitory and clustering effects throughout different time points. Our analysis framework is applicable to a wide variety of spatially-resolved transcriptomic data to derive biological insights.
The biotrophic fungal pathogen Blumeria graminis causes the powdery mildew disease of cereals and grasses. Proteins with a predicted ribonuclease (RNase)-like fold (termed RALPHs) comprise the largest set of secreted effector candidates within the B. graminis f. sp. hordei genome. Their exceptional abundance suggests they play crucial functions during pathogenesis. We show that transgenic expression of RALPH CSEP0064/BEC1054 increases susceptibility to infection in monocotyledenous and dicotyledonous plants. CSEP0064/BEC1054 interacts in planta with five host proteins: two translation elongation factors (eEF1 and eEF1{gamma}), two pathogenesis-related proteins (PR5 and PR10) and a glutathione-S-transferase. We present the first crystal structure of a RALPH, CSEP0064/BEC1054, demonstrating it has an RNase-like fold. The protein interacts with total RNA and weakly with DNA. Methyl jasmonate levels modulate susceptibility to aniline-induced host RNA fragmentation. In planta expression of CSEP0064/BEC1054 reduces the formation of this RNA fragment. We propose that CSEP0064/BEC1054 is a pseudoenzyme that binds to host ribosomes, thereby inhibiting the action of plant ribosome-inactivating proteins that would otherwise lead to host cell death, an unviable interaction and demise of the fungus.
Pathogen build-up in vegetative planting material, termed seed degeneration, is a major problem in many low-income countries. When smallholder farmers use seed produced on-farm or acquired outside certified programs, it is often infected. We introduce a risk assessment framework for seed degeneration, evaluating the relative performance of individual and combined components of an integrated seed health strategy. The frequency distribution of management performance outcomes was evaluated for models incorporating biological and environmental heterogeneity, with the following results. (1) On-farm seed selection can perform as well as certified seed, if the rate of success in selecting healthy plants for seed production is high; (2) When choosing among within-season management strategies, external inoculum can determine the relative usefulness of incidence-altering management (affecting the proportion of diseased plants/seeds) and rate-altering management (affecting the rate of disease transmission in the field); (3) Under severe disease scenarios, where it is difficult to implement management components at high levels of effectiveness, combining management components can produce synergistic benefits and keep seed degeneration below a threshold; (4) Combining management components can also close the yield gap between average and worst-case scenarios. We also illustrate the potential for expert elicitation to provide parameter estimates when data are unavailable.