Transcriptome dynamics of CD4+ T cells during malaria maps gradual transit from effector to memory.

The dynamics of CD4+ T cell memory development remain to be examined at genome scale. In malaria-endemic regions, antimalarial chemoprevention protects long after its cessation and associates with effects on CD4+ T cells. We applied single-cell RNA sequencing and computational modelling to track memory development during Plasmodium infection and treatment. In the absence of central memory precursors, two trajectories developed as T helper 1 (TH1) and follicular helper T (TFH) transcriptomes contracted and partially coalesced over three weeks. Progeny of single clones populated TH1 and TFH trajectories, and fate-mapping suggested that there was minimal lineage plasticity. Relationships between TFH and central memory were revealed, with antimalarials modulating these responses and boosting TH1 recall. Finally, single-cell epigenomics confirmed that heterogeneity among effectors was partially reset in memory. Thus, the effector-to-memory transition in CD4+ T cells is gradual during malaria and is modulated by antiparasitic drugs. Graphical user interfaces are presented for examining gene-expression dynamics and gene-gene correlations ( http://haquelab.mdhs.unimelb.edu.au/cd4_memory/ ).

Human degradation of tropical moist forests is greater than previously estimated.

Tropical forest degradation from selective logging, fire and edge effects is a major driver of carbon and biodiversity loss1-3, with annual rates comparable to those of deforestation4. However, its actual extent and long-term impacts remain uncertain at global tropical scale5. Here we quantify the magnitude and persistence of multiple types of degradation on forest structure by combining satellite remote sensing data on pantropical moist forest cover changes4 with estimates of canopy height and biomass from spaceborne6 light detection and ranging (LiDAR). We estimate that forest height decreases owing to selective logging and fire by 15% and 50%, respectively, with low rates of recovery even after 20 years. Agriculture and road expansion trigger a 20% to 30% reduction in canopy height and biomass at the forest edge, with persistent effects being measurable up to 1.5 km inside the forest. Edge effects encroach on 18% (approximately 206 Mha) of the remaining tropical moist forests, an area more than 200% larger than previously estimated7. Finally, degraded forests with more than 50% canopy loss are significantly more vulnerable to subsequent deforestation. Collectively, our findings call for greater efforts to prevent degradation and protect already degraded forests to meet the conservation pledges made at recent United Nations Climate Change and Biodiversity conferences.

Chandrayaan-3 APXS elemental abundance measurements at lunar high latitude.

The elemental composition of the lunar surface provides insights into mechanisms of the formation and evolution of the Moon1,2. The chemical composition of lunar regolith have so far been precisely measured using the samples collected by the Apollo, Luna and Chang'e 5 missions, which are from equatorial to mid-latitude regions3,4; lunar meteorites, whose location of origin on the Moon is unknown5,6; and the in situ measurement from the Chang'e 3 and Chang'e 4 missions7-9, which are from the mid-latitude regions of the Moon. Here we report the first in situ measurements of the elemental abundances in the lunar southern high-latitude regions by the Alpha Particle X-ray Spectrometer (APXS) experiment10 aboard the Pragyan rover of India's Chandrayaan-3 mission. The 23 measurements in the vicinity of the Chandrayaan-3 landing site show that the local lunar terrain in this region is fairly uniform and primarily composed of ferroan anorthosite (FAN), a product of the lunar magma ocean (LMO) crystallization. However, observation of relatively higher magnesium abundance with respect to calcium in APXS measurements suggests the mixing of further mafic material. The compositional uniformity over a few tens of metres around the Chandrayaan-3 landing site provides an excellent ground truth for remote-sensing observations.

Observation of the effect of gravity on the motion of antimatter.

Einstein's general theory of relativity from 19151 remains the most successful description of gravitation. From the 1919 solar eclipse2 to the observation of gravitational waves3, the theory has passed many crucial experimental tests. However, the evolving concepts of dark matter and dark energy illustrate that there is much to be learned about the gravitating content of the universe. Singularities in the general theory of relativity and the lack of a quantum theory of gravity suggest that our picture is incomplete. It is thus prudent to explore gravity in exotic physical systems. Antimatter was unknown to Einstein in 1915. Dirac's theory4 appeared in 1928; the positron was observed5 in 1932. There has since been much speculation about gravity and antimatter. The theoretical consensus is that any laboratory mass must be attracted6 by the Earth, although some authors have considered the cosmological consequences if antimatter should be repelled by matter7-10. In the general theory of relativity, the weak equivalence principle (WEP) requires that all masses react identically to gravity, independent of their internal structure. Here we show that antihydrogen atoms, released from magnetic confinement in the ALPHA-g apparatus, behave in a way consistent with gravitational attraction to the Earth. Repulsive 'antigravity' is ruled out in this case. This experiment paves the way for precision studies of the magnitude of the gravitational acceleration between anti-atoms and the Earth to test the WEP.

Superconducting-qubit readout via low-backaction electro-optic transduction.

Entangling microwave-frequency superconducting quantum processors through optical light at ambient temperature would enable means of secure communication and distributed quantum information processing1. However, transducing quantum signals between these disparate regimes of the electro-magnetic spectrum remains an outstanding goal2-9, and interfacing superconducting qubits, which are constrained to operate at millikelvin temperatures, with electro-optic transducers presents considerable challenges owing to the deleterious effects of optical photons on superconductors9,10. Moreover, many remote entanglement protocols11-14 require multiple qubit gates both preceding and following the upconversion of the quantum state, and thus an ideal transducer should impart minimal backaction15 on the qubit. Here we demonstrate readout of a superconducting transmon qubit through a low-backaction electro-optomechanical transducer. The modular nature of the transducer and circuit quantum electrodynamics system used in this work enable complete isolation of the qubit from optical photons, and the backaction on the qubit from the transducer is less than that imparted by thermal radiation from the environment. Moderate improvements in the transducer bandwidth and the added noise will enable us to leverage the full suite of tools available in circuit quantum electrodynamics to demonstrate transduction of non-classical signals from a superconducting qubit to the optical domain.

RNA profiles reveal signatures of future health and disease in pregnancy.

Maternal morbidity and mortality continue to rise, and pre-eclampsia is a major driver of this burden1. Yet the ability to assess underlying pathophysiology before clinical presentation to enable identification of pregnancies at risk remains elusive. Here we demonstrate the ability of plasma cell-free RNA (cfRNA) to reveal patterns of normal pregnancy progression and determine the risk of developing pre-eclampsia months before clinical presentation. Our results centre on comprehensive transcriptome data from eight independent prospectively collected cohorts comprising 1,840 racially diverse pregnancies and retrospective analysis of 2,539 banked plasma samples. The pre-eclampsia data include 524 samples (72 cases and 452 non-cases) from two diverse independent cohorts collected 14.5 weeks (s.d., 4.5 weeks) before delivery. We show that cfRNA signatures from a single blood draw can track pregnancy progression at the placental, maternal and fetal levels and can robustly predict pre-eclampsia, with a sensitivity of 75% and a positive predictive value of 32.3% (s.d., 3%), which is superior to the state-of-the-art method2. cfRNA signatures of normal pregnancy progression and pre-eclampsia are independent of clinical factors, such as maternal age, body mass index and race, which cumulatively account for less than 1% of model variance. Further, the cfRNA signature for pre-eclampsia contains gene features linked to biological processes implicated in the underlying pathophysiology of pre-eclampsia.

An aged immune system drives senescence and ageing of solid organs.

Ageing of the immune system, or immunosenescence, contributes to the morbidity and mortality of the elderly1,2. To define the contribution of immune system ageing to organism ageing, here we selectively deleted Ercc1, which encodes a crucial DNA repair protein3,4, in mouse haematopoietic cells to increase the burden of endogenous DNA damage and thereby senescence5-7 in the immune system only. We show that Vav-iCre+/-;Ercc1-/fl mice were healthy into adulthood, then displayed premature onset of immunosenescence characterized by attrition and senescence of specific immune cell populations and impaired immune function, similar to changes that occur during ageing in wild-type mice8-10. Notably, non-lymphoid organs also showed increased senescence and damage, which suggests that senescent, aged immune cells can promote systemic ageing. The transplantation of splenocytes from Vav-iCre+/-;Ercc1-/fl or aged wild-type mice into young mice induced senescence in trans, whereas the transplantation of young immune cells attenuated senescence. The treatment of Vav-iCre+/-;Ercc1-/fl mice with rapamycin reduced markers of senescence in immune cells and improved immune function11,12. These data demonstrate that an aged, senescent immune system has a causal role in driving systemic ageing and therefore represents a key therapeutic target to extend healthy ageing.

Laser cooling of antihydrogen atoms.

The photon-the quantum excitation of the electromagnetic field-is massless but carries momentum. A photon can therefore exert a force on an object upon collision1. Slowing the translational motion of atoms and ions by application of such a force2,3, known as laser cooling, was first demonstrated 40 years ago4,5. It revolutionized atomic physics over the following decades6-8, and it is now a workhorse in many fields, including studies on quantum degenerate gases, quantum information, atomic clocks and tests of fundamental physics. However, this technique has not yet been applied to antimatter. Here we demonstrate laser cooling of antihydrogen9, the antimatter atom consisting of an antiproton and a positron. By exciting the 1S-2P transition in antihydrogen with pulsed, narrow-linewidth, Lyman-α laser radiation10,11, we Doppler-cool a sample of magnetically trapped antihydrogen. Although we apply laser cooling in only one dimension, the trap couples the longitudinal and transverse motions of the anti-atoms, leading to cooling in all three dimensions. We observe a reduction in the median transverse energy by more than an order of magnitude-with a substantial fraction of the anti-atoms attaining submicroelectronvolt transverse kinetic energies. We also report the observation of the laser-driven 1S-2S transition in samples of laser-cooled antihydrogen atoms. The observed spectral line is approximately four times narrower than that obtained without laser cooling. The demonstration of laser cooling and its immediate application has far-reaching implications for antimatter studies. A more localized, denser and colder sample of antihydrogen will drastically improve spectroscopic11-13 and gravitational14 studies of antihydrogen in ongoing experiments. Furthermore, the demonstrated ability to manipulate the motion of antimatter atoms by laser light will potentially provide ground-breaking opportunities for future experiments, such as anti-atomic fountains, anti-atom interferometry and the creation of antimatter molecules.

Molecular and clinical presentation of UBA1-mutated myelodysplastic syndromes.

ABSTRACT: Mutations in UBA1, which are disease-defining for VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) syndrome, have been reported in patients diagnosed with myelodysplastic syndromes (MDS). Here, we define the prevalence and clinical associations of UBA1 mutations in a representative cohort of patients with MDS. Digital droplet polymerase chain reaction profiling of a selected cohort of 375 male patients lacking MDS disease-defining mutations or established World Health Organization (WHO) disease classification identified 28 patients (7%) with UBA1 p.M41T/V/L mutations. Using targeted sequencing of UBA1 in a representative MDS cohort (n = 2027), we identified an additional 27 variants in 26 patients (1%), which we classified as likely/pathogenic (n = 12) and of unknown significance (n = 15). Among the total 40 patients with likely/pathogenic variants (2%), all were male and 63% were classified by WHO 2016 criteria as MDS with multilineage dysplasia or MDS with single-lineage dysplasia. Patients had a median of 1 additional myeloid gene mutation, often in TET2 (n = 12), DNMT3A (n = 10), ASXL1 (n = 3), or SF3B1 (n = 3). Retrospective clinical review, where possible, showed that 82% (28/34) UBA1-mutant cases had VEXAS syndrome-associated diagnoses or inflammatory clinical presentation. The prevalence of UBA1 mutations in patients with MDS argues for systematic screening for UBA1 in the management of MDS.

Molecular Taxonomy of Myelodysplastic Syndromes and its Clinical Implications.

Myelodysplastic syndromes/neoplasms (MDS) are clonal hematologic disorders characterized by morphologic abnormalities of myeloid cells and peripheral cytopenias. While genetic abnormalities underlie the pathogenesis of these disorders and their heterogeneity, current classifications of MDS rely predominantly on morphology. We performed genomic profiling of 3,233 patients with MDS or related disorders to delineate molecular subtypes and define their clinical implications. Gene mutations, copy-number alterations (CNAs), and copy-neutral loss of heterozygosity (cnLOH) were derived from targeted sequencing of a 152-gene panel, with abnormalities identified in 91, 43, and 11% of patients, respectively. We characterized 16 molecular groups, encompassing 86% of patients, using information from 21 genes, 6 cytogenetic events, and LOH at the TP53 and TET2 loci. Two residual groups defined by negative findings (molecularly not-otherwise specified, absence of recurrent drivers) comprised 14% of patients. The groups varied in size from 0.5% to 14% of patients and were associated with distinct clinical phenotypes and outcomes. The median bone marrow blast percentage across groups ranged from 1.5 to 10%, and the median overall survival from 0.9 to 8.2 years. We validated 5 well-characterized entities, added further evidence to support 3 previously reported subsets, and described 8 novel groups. The prognostic influence of bone marrow blasts depended on the genetic subtypes. Within genetic subgroups, therapy-related MDS and myelodysplastic/myeloproliferative neoplasms (MDS/MPN) had comparable clinical and outcome profiles to primary MDS. In conclusion, genetically-derived subgroups of MDS are clinically relevant and may inform future classification schemas and translational therapeutic research.

PypKa server: online pKa predictions and biomolecular structure preparation with precomputed data from PDB and AlphaFold DB.

When preparing biomolecular structures for molecular dynamics simulations, pKa calculations are required to provide at least a representative protonation state at a given pH value. Neglecting this step and adopting the reference protonation states of the amino acid residues in water, often leads to wrong electrostatics and nonphysical simulations. Fortunately, several methods have been developed to prepare structures considering the protonation preference of residues in their specific environments (pKa values), and some are even available for online usage. In this work, we present the PypKa server, which allows users to run physics-based, as well as ML-accelerated methods suitable for larger systems, to obtain pKa values, isoelectric points, titration curves, and structures with representative pH-dependent protonation states compatible with commonly used force fields (AMBER, CHARMM, GROMOS). The user may upload a custom structure or submit an identifier code from PBD or UniProtKB. The results for over 200k structures taken from the Protein Data Bank and the AlphaFold DB have been precomputed, and their data can be retrieved without extra calculations. All this information can also be obtained from an application programming interface (API) facilitating its usage and integration into existing pipelines as well as other web services. The web server is available at pypka.org.

Enhancing GABAergic Tonic Inhibition Reduces Seizure-Like Activity in the Neonatal Mouse Hippocampus and Neocortex.

Approximately one-third of neonatal seizures do not respond to first-line anticonvulsants, including phenobarbital, which enhances phasic inhibition. Whether enhancing tonic inhibition decreases seizure-like activity in the neonate when GABA is mainly depolarizing at this age is unknown. We evaluated if increasing tonic inhibition using THIP [4,5,6,7-tetrahydroisoxazolo(5,4-c)pyridin-3-ol, gaboxadol], a δ-subunit-selective GABAA receptor agonist, decreases seizure-like activity in neonatal C57BL/6J mice (postnatal day P5-8, both sexes) using acute brain slices. Whole-cell patch-clamp recordings showed that THIP enhanced GABAergic tonic inhibitory conductances in layer V neocortical and CA1 pyramidal neurons and increased their rheobase without altering sEPSC characteristics. Two-photon calcium imaging demonstrated that enhancing the activity of extrasynaptic GABAARs decreased neuronal firing in both brain regions. In the 4-aminopyridine and the low-Mg2+ model of pharmacoresistant seizures, THIP reduced epileptiform activity in the neocortex and CA1 hippocampal region of neonatal and adult brain slices in a dose-dependent manner. We conclude that neocortical layer V and CA1 pyramidal neurons have tonic inhibitory conductances, and when enhanced, they reduce neuronal firing and decrease seizure-like activity. Therefore, augmenting tonic inhibition could be a viable approach for treating neonatal seizures.

Temporary mechanical circulatory support in infarct-related cardiogenic shock: an individual patient data meta-analysis of randomised trials with 6-month follow-up.

BACKGROUND: Percutaneous active mechanical circulatory support (MCS) devices are being increasingly used in the treatment of acute myocardial infarction-related cardiogenic shock (AMICS) despite conflicting evidence regarding their effect on mortality. We aimed to ascertain the effect of early routine active percutaneous MCS versus control treatment on 6-month all-cause mortality in patients with AMICS. METHODS: In this individual patient data meta-analysis, randomised controlled trials of potential interest were identified, without language restriction, by querying the electronic databases MEDLINE via PubMed, Cochrane Central Register of Controlled Trials, and Embase, as well as ClinicalTrials.gov, up to Jan 26, 2024. All randomised trials with 6-month mortality data comparing early routine active MCS (directly in the catheterisation laboratory after randomisation) versus control in patients with AMICS were included. The primary outcome was 6-month all-cause mortality in patients with AMICS treated with early routine active percutaneous MCS versus control, with a focus on device type (loading, such as venoarterial extracorporeal membrane oxygenation [VA-ECMO] vs unloading) and patient selection. Hazard ratios (HRs) of the primary outcome measure were calculated using Cox regression models. This study is registered with PROSPERO, CRD42024504295. FINDINGS: Nine reports of randomised controlled trials (n=1114 patients) were evaluated in detail. Overall, four randomised controlled trials (n=611 patients) compared VA-ECMO with a control treatment and five randomised controlled trials (n=503 patients) compared left ventricular unloading devices with a control treatment. Two randomised controlled trials also included patients who did not have AMICS, who were excluded (55 patients [44 who were treated with VA-ECMO and 11 who were treated with a left ventricular unloading device]). The median patient age was 65 years (IQR 57-73); 845 (79·9%) of 1058 patients with data were male and 213 (20·1%) were female. No significant benefit of early unselected MCS use on 6-month mortality was noted (HR 0·87 [95% CI 0·74-1·03]; p=0·10). No significant differences were observed for left ventricular unloading devices versus control (0·80 [0·62-1·02]; p=0·075), and loading devices also had no effect on mortality (0·93 [0·75-1·17]; p=0·55). Patients with ST-elevation cardiogenic shock without risk of hypoxic brain injury had a reduction in mortality with MCS use (0·77 [0·61-0·97]; p=0·024). Major bleeding (odds ratio 2·64 [95% CI 1·91-3·65]) and vascular complications (4·43 [2·37-8·26]) were more frequent with MCS use than with control. INTERPRETATION: The use of active MCS devices in patients with AMICS did not reduce 6-month mortality (regardless of the device used) and increased major bleeding and vascular complications. However, patients with ST-elevation cardiogenic shock without risk of hypoxic brain injury had a reduction in mortality after MCS use. Therefore, the use of MCS should be restricted to certain patients only. FUNDING: The Heart Center Leipzig at Leipzig University and the Foundation Institut für Herzinfarktforschung.

Intratumoral Cell Neighborhoods Coordinate Outcomes in Pancreatic Ductal Adenocarcinoma.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDA) is a highly lethal disease characterized by a spatially heterogeneous tumor microenvironment. Within the PDA microenvironment, cells organize into communities where cell fate is influenced by neighboring cells of diverse ontogeny and function. However, it remains unclear how cell neighborhoods in the tumor microenvironment evolve with treatment and impact clinical outcomes. METHODS: Here, using automated chromogenic multiplex immunohistochemistry and unsupervised computational image analysis of human PDA tumors, we investigated cell neighborhoods in surgically resected tumors from patients with chemotherapy-naïve PDA (n = 59) and neoadjuvant chemotherapy-treated PDA (n = 57). Single cells were defined by lineage markers (CD3, CD8, Foxp3, CD68, CK19), proliferation (Ki67), and neighboring cells. RESULTS: Distinct intratumoral immune and tumor cell subsets were defined by neighboring cells. Higher content of stromal-associated macrophages was seen in chemotherapy-naïve tumors from long-term survivors (overall survival >3 years) compared with short-term survivors (overall survival <1 year), whereas immune-excluded tumor cells were higher in short-term survivors. Chemotherapy-treated vs -naïve tumors showed lower content of tumor-associated T cells and macrophages but similar densities of stromal-associated immune cells. However, proliferating tumor cell subsets with immune-rich neighborhoods were higher in chemotherapy-treated tumors. In a blinded analysis of tumors from patients treated with neoadjuvant chemotherapy, a composite index comprising lower quantities of immune-excluded tumor cells and higher spatially distinct immune cell subsets was associated with prolonged survival. CONCLUSIONS: Together, these data provide new insights into discrete cell communities in PDA and show their clinical relevance.

Advances in the field of phage-based therapy with special emphasis on computational resources.

In the current era, one of the major challenges is to manage the treatment of drug/antibiotic-resistant strains of bacteria. Phage therapy, a century-old technique, may serve as an alternative to antibiotics in treating bacterial infections caused by drug-resistant strains of bacteria. In this review, a systematic attempt has been made to summarize phage-based therapy in depth. This review has been divided into the following two sections: general information and computer-aided phage therapy (CAPT). In the case of general information, we cover the history of phage therapy, the mechanism of action, the status of phage-based products (approved and clinical trials) and the challenges. This review emphasizes CAPT, where we have covered primary phage-associated resources, phage prediction methods and pipelines. This review covers a wide range of databases and resources, including viral genomes and proteins, phage receptors, host genomes of phages, phage-host interactions and lytic proteins. In the post-genomic era, identifying the most suitable phage for lysing a drug-resistant strain of bacterium is crucial for developing alternate treatments for drug-resistant bacteria and this remains a challenging problem. Thus, we compile all phage-associated prediction methods that include the prediction of phages for a bacterial strain, the host for a phage and the identification of interacting phage-host pairs. Most of these methods have been developed using machine learning and deep learning techniques. This review also discussed recent advances in the field of CAPT, where we briefly describe computational tools available for predicting phage virions, the life cycle of phages and prophage identification. Finally, we describe phage-based therapy's advantages, challenges and opportunities.

DMPPred: a tool for identification of antigenic regions responsible for inducing type 1 diabetes mellitus.

There are a number of antigens that induce autoimmune response against ß-cells, leading to type 1 diabetes mellitus (T1DM). Recently, several antigen-specific immunotherapies have been developed to treat T1DM. Thus, identification of T1DM associated peptides with antigenic regions or epitopes is important for peptide based-therapeutics (e.g. immunotherapeutic). In this study, for the first time, an attempt has been made to develop a method for predicting, designing, and scanning of T1DM associated peptides with high precision. We analysed 815 T1DM associated peptides and observed that these peptides are not associated with a specific class of HLA alleles. Thus, HLA binder prediction methods are not suitable for predicting T1DM associated peptides. First, we developed a similarity/alignment based method using Basic Local Alignment Search Tool and achieved a high probability of correct hits with poor coverage. Second, we developed an alignment-free method using machine learning techniques and got a maximum AUROC of 0.89 using dipeptide composition. Finally, we developed a hybrid method that combines the strength of both alignment free and alignment-based methods and achieves maximum area under the receiver operating characteristic of 0.95 with Matthew's correlation coefficient of 0.81 on an independent dataset. We developed a web server 'DMPPred' and stand-alone server for predicting, designing and scanning T1DM associated peptides (https://webs.iiitd.edu.in/raghava/dmppred/).

Prediction of RNA-interacting residues in a protein using CNN and evolutionary profile.

This paper describes a method Pprint2, which is an improved version of Pprint developed for predicting RNA-interacting residues in a protein. Training and independent/validation datasets used in this study comprises of 545 and 161 non-redundant RNA-binding proteins, respectively. All models were trained on training dataset and evaluated on the validation dataset. The preliminary analysis reveals that positively charged amino acids such as H, R and K, are more prominent in the RNA-interacting residues. Initially, machine learning based models have been developed using binary profile and obtain maximum area under curve (AUC) 0.68 on validation dataset. The performance of this model improved significantly from AUC 0.68 to 0.76, when evolutionary profile is used instead of binary profile. The performance of our evolutionary profile-based model improved further from AUC 0.76 to 0.82, when convolutional neural network has been used for developing model. Our final model based on convolutional neural network using evolutionary information achieved AUC 0.82 with Matthews correlation coefficient of 0.49 on the validation dataset. Our best model outperforms existing methods when evaluated on the independent/validation dataset. A user-friendly standalone software and web-based server named 'Pprint2' has been developed for predicting RNA-interacting residues (https://webs.iiitd.edu.in/raghava/pprint2 and https://github.com/raghavagps/pprint2).

A noncanonical enzymatic function of PIWIL4 maintains genomic integrity and leukemic growth in AML.

RNA-binding proteins (RBPs) form a large and diverse class of factors, many members of which are overexpressed in hematologic malignancies. RBPs participate in various processes of messenger RNA (mRNA) metabolism and prevent harmful DNA:RNA hybrids or R-loops. Here, we report that PIWIL4, a germ stem cell-associated RBP belonging to the RNase H-like superfamily, is overexpressed in patients with acute myeloid leukemia (AML) and is essential for leukemic stem cell function and AML growth, but dispensable for healthy human hematopoietic stem cells. In AML cells, PIWIL4 binds to a small number of known piwi-interacting RNA. Instead, it largely interacts with mRNA annotated to protein-coding genic regions and enhancers that are enriched for genes associated with cancer and human myeloid progenitor gene signatures. PIWIL4 depletion in AML cells downregulates the human myeloid progenitor signature and leukemia stem cell (LSC)-associated genes and upregulates DNA damage signaling. We demonstrate that PIWIL4 is an R-loop resolving enzyme that prevents R-loop accumulation on a subset of AML and LSC-associated genes and maintains their expression. It also prevents DNA damage, replication stress, and activation of the ATR pathway in AML cells. PIWIL4 depletion potentiates sensitivity to pharmacological inhibition of the ATR pathway and creates a pharmacologically actionable dependency in AML cells.

The single-cell opioid responses in the context of HIV (SCORCH) consortium.

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

Enlightening the Path to Protein Engineering: Chemoselective Turn-On Probes for High-Throughput Screening of Enzymatic Activity.

Many successful stories in enzyme engineering are based on the creation of randomized diversity in large mutant libraries, containing millions to billions of enzyme variants. Methods that enabled their evaluation with high throughput are dominated by spectroscopic techniques due to their high speed and sensitivity. A large proportion of studies relies on fluorogenic substrates that mimic the chemical properties of the target or coupled enzymatic assays with an optical read-out that assesses the desired catalytic efficiency indirectly. The most reliable hits, however, are achieved by screening for conversions of the starting material to the desired product. For this purpose, functional group assays offer a general approach to achieve a fast, optical read-out. They use the chemoselectivity, differences in electronic and steric properties of various functional groups, to reduce the number of false-positive results and the analytical noise stemming from enzymatic background activities. This review summarizes the developments and use of functional group probes for chemoselective derivatizations, with a clear focus on screening for enzymatic activity in protein engineering.