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Pereira, J.

Publications and source records attributed to Pereira, J..

At least 19 recordsLinked to original sources

Mitigation of intertidal temperature extremes by algal canopies

In a rapidly warming world, species must either adapt to changing environmental conditions, shift their distributions through the movement and survival of individuals, or face local or global extinction. Within ecosystems, structural complexity of either environmental or biogenic origin may provide microclimate buffering, promoting persistence. In coastal environments, it has long been stated that macroalgae act as important ecosystem engineers that can moderate thermal extremes, however the magnitude of this buffering has rarely been quantified. Moreover, the extent to which thermal buffering varies among macroalgal species, and how it relates to thermal heterogeneity across scales remains poorly understood. Here, we measured thermal buffering provided by intertidal macroalgae using high-frequency, high-spatial-resolution in situ temperature logging. We compared microclimates beneath algal cover with those on experimentally cleared bare rock across two tidal levels, two solar exposures and two seasons along six shores within a biogeographical transition zone. Thermal buffering was highly heterogeneous across the study area, varying with species identity, algal cover, tidal level, and solar exposure. Together, these factors generated a complex thermal mosaic, with even small algal specimens providing measurable buffering. We found that latitude had little influence on mean daytime low-tide temperatures, whereas local-scale factors had pronounced effects. Lower tidal position, reduced solar exposure, and algal cover each moderated thermal conditions and, in combination, provided an average cooling of approximately 4 {degrees}C. These findings highlight the importance of fine-scale habitat heterogeneity in shaping thermal exposure and identify features that could be incorporated into local climate-adaptation strategies, supporting coastal conservation and restoration efforts.

ecology↗

Automated pup-level analysis reveals distinct effects of prenatal CBD and THC exposure on maternal retrieval

This study examined how prenatal CBD and {Delta}9-tetrahydrocannabinol (THC) exposure affects maternal caregiving in C57BL/6J mice. We developed the Machine-Automated Scoring of the Pup Retrieval Test (MAS-PRT) to overcome limitations of manual behavioral scoring. MAS-PRT integrates Multi-Animal DeepLabCut for dam and pup tracking with Detectron2 for dynamic nest reconstruction. Validated against 170 manually annotated retrieval trials, the pipeline showed high concordance with manual measurements and enabled reproducible extraction of encounter latency, retrieval latency, and locomotor trajectories. Prenatal exposure did not impair general nest-building or overall home-cage maternal care. However, pups from both CBD and THC groups showed reduced body weight at postnatal day 5. Cox proportional hazards modeling revealed divergent effects by compound: CBD-exposed dams exhibited a weight-dependent increase in probability of encountering and retrieving lighter pups, independent of pup sex. Spatial tracking further showed that dams traversed significantly shorter total trajectories when retrieving female progeny exposed to either compound. Longitudinal trial-by-trial analysis indicated intact task acquisition in controls and CBD dams, whereas THC dams displayed a flattened learning curve driven by lower retrieval latencies on initial trials. Together, these findings indicate that prenatal cannabinoid exposure does not produce generalized disruption of maternal care but instead induces compound-specific alterations in maternal reactivity, retrieval kinematics, and learning dynamics.

animal behavior and cognition↗

All signals considered: Data quality partially explains inter-individual task differences in a large, open fNIRS dataset

Significance: High inter-subject variability and limited reproducibility in functional near-infrared spectroscopy (fNIRS) research may partly reflect global systemic physiology and signal quality differences, possibly distorting task-evoked hemodynamic responses. Aim: We investigate how signal quality relates to inter-subject variability in motor-task fNIRS responses and introduce a large, open, multi-task, near whole-head fNIRS dataset with extensive peripheral physiology and short-channel recordings. Approach: Fifty-seven participants completed resting-state, motor action, motor imagery, emotion recognition, visual, and auditory tasks during fNIRS recording. Peripheral measures included pulse oximetry, heart rate, blood oxygen saturation, respiration, room temperature, galvanic skin response, electrocardiogram, and electromyography. Signal quality was assessed using the scalp coupling index (SCI), coefficient of variation (CV), signal-to-noise ratio (SNR) and a spectral measure here coined the coupling SNR (cSNR). Results: Quality metrics were weakly to moderately correlated, except SNR and CV, which showed the expected inverse relationship. All quality metrics were significantly related to channel length and associated with task-related activation estimates. Group-level analyses validated activation in expected task-related regions. Conclusions: The assessed metrics capture complementary features of fNIRS signal quality and may help explain individual activation differences. The dataset provides a comprehensive, open resource enabling future evaluation of physiological correction methods and confound mitigation.

neuroscience↗

FDXR Upregulation by p63/p73 is a Prognostic and Therapeutic Marker of HTLV-1-Associated Adult T Cell Leukemia/Lymphoma

Infection with human T-lymphotropic virus 1 (HTLV-1) can lead to severe diseases, including adult T-cell leukemia/lymphoma (ATL), for which current therapies are inadequate. HTLV-1 persists chronically through integration of its genome into host DNA and expansion of infected clones via cellular proliferation. Selective elimination of infected cells is the ideal treatment goal but requires identifying cellular markers dysregulated by HTLV-1 that can be exploited therapeutically. Combining metabolomics and proteomics analyses, we identified increased expression of the mitochondrial enzyme ferredoxin reductase (FDXR) as a hallmark of HTLV-1-infected cells. In patient cells, FDXR upregulation mirrored disease severity, was enriched in proliferating tumour cells and predicted worse ATL prognosis. Mechanistically, FDXR upregulation was directly driven by the transactivating isoforms of two p53 family members, TAp63 and TAp73. In silico drug susceptibility predictions, followed by targeted cytotoxicity, proliferation and Drug-Seq assays demonstrated that FDXR upregulation is associated with increased sensitivity of ATL cells to repurposed chemotherapeutic agents, particularly fluorouracil. Overall, our findings establish FDXR as a novel biomarker of HTLV-1-associated disease progression and ATL prognosis, elucidate its upstream molecular regulation, and highlight its predictive potential for chemotherapeutic sensitivity of ATL cells.

microbiology↗

Independent Component Analysis Outperforms Seed-Based Approach in Detecting fNIRS-based Resting-State Functional Connectivity

SignificanceResting-state functional connectivity (RSFC) is an important measure in advancing our understanding of brain function and development as well as various neurological and mental disorders. Studying RSFC with functional near-infrared spectroscopy (fNIRS) offers several advantages over functional magnetic resonance imaging (fMRI), especially for clinical and pediatric populations. However, the optimal strategy to estimate RSFC based on fNIRS, particularly in identifying reliable connectivity patterns across chromophores, remains unclear. Establishing robust analysis approaches is essential for reliable and clinically meaningful applications. AimThis study systematically evaluated commonly used analysis methods regarding their effectiveness to detect RSFC patterns within the motor network using both oxygenated (HbO) and deoxygenated (HbR) hemoglobin signals. ApproachNear whole-head resting-state fNIRS data were analyzed from 38 participants. RSFC was estimated with five analytical approaches: three seed-based methods (SBA-GLM, SBA-GLM with respiratory regression, and SBA-correlation) and two independent component analyses (ICA) approaches using two different contrast functions. Performance was assessed via receiver operating characteristic analyses based on both anatomical and functional definitions of motor-related connectivity. Areas under the curves (AUC) were statistically compared with DeLongs test, and the spatial similarity between HbO and HbR RSFC was quantified by correlating RSFC patterns from the two chromophores. ResultsAcross reference definitions and chromophores, ICA consistently achieved higher performance (AUC = 0.82-0.96) in detecting motor-related RSFC than SBA (AUC = 0.63-0.86). Significant differences emerged when functionally defined connectivity references were used, with ICA outperforming SBA across chromophores. Under certain condition, correlational-SBA (AUC = 0.66-0.86) significantly outperformed GLM-based methods (AUC = 0.63-0.85). Finally, ICA results demonstrated greater spatial similarity between obtained HbO and HbR RSFC patterns (r = 0.90-0.92) than SBA (r = 0.84-0.86), indicating higher cross-chromophore consistency. ConclusionsICA provides a robust and consistent framework for estimating fNIRS-based RSFC across both HbO and HbR, outperforming SBA in accuracy and cross-chromophore consistency. While correlational-SBA offers a computationally efficient alternative and outperforms GLM-based methods, ICA should be preferred when reliable and chromophore-consistent RSFC estimates are required. Importantly, these findings demonstrate that HbR contains RSFC information comparable to HbO and highlights the critical role of analytical strategy and reference definition in RSFC evaluation. Collectively, these results contribute to the methodological standardization of fNIRS-based RSFC and support its use in future neuroscientific and clinical applications.

neuroscience↗

Functional Profiling of Kiwifruit Phyllosphere Bacteria: Copper Resistance and Biocontrol Potential as a Foundation for Microbiome-Informed Strategies

Bacterial canker, caused by Pseudomonas syringae pv. actinidiae (Psa) is a major threat to global kiwifruit production. Copper-based bactericides remain widely used, but increasing resistance underscores the need for alternative strategies. Understanding the functional capabilities of phyllosphere bacteria under copper pressure is critical for designing sustainable alternatives. This study provides a culture-based functional inventory of bacteria associated with Actinidia chinensis var. deliciosa leaves from Portuguese orchards under long-term copper management, aiming to identify native taxa with traits relevant to plant health and resilience. A total of 1,058 isolates were recovered and grouped into 261 RAPD clusters, representing 58 species across 29 genera. Representative strains were screened for plant growth-promoting (PGP) traits (IAA, siderophore production, phosphate solubilization, ammonia production), copper tolerance, and in vitro antagonism against Psa. Copper resistance was widespread (53.3% of isolates with MIC [≥]0.8 mM), including the first evidence of a highly copper-resistant PSA in Portuguese kiwifruit orchards and an exceptionally resistant non-pathogenic strain (Erwinia iniecta, MIC 2.8 mM). A subset of 25 isolates combined all PGP traits. In parallel, several isolates exhibited antagonism against Psa, including Bacillus pumilus, which consistently inhibited pathogen growth. Notably, some antagonistic isolates overlapped with the multifunctional PGP subset, highlighting promising candidates for integrated biocontrol strategies. These findings reveal the kiwifruit phyllosphere as a reservoir of functionally diverse and copper-resilient bacteria, highlighting both ecological risks and opportunities for microbiome-based biocontrol innovation. This work establishes a functional baseline for future in planta validation and microbiome-informed disease management strategies.

microbiology↗

Loss of Vitellogenin Receptor Function Results in Yolk Depletion, Virome Expansion and Reduced Bacterial Load Within the Oocytes of Rhodnius prolixus

The vitellogenin receptor (VgR) mediates yolk protein uptake during oogenesis and is essential for embryogenesis in oviparous species. Here we characterize the single Rhodnius prolixus VgR isoform and uncover an unexpected role in microbial regulation within the reproductive system. The receptor displays a conserved LDLR-like structure and is highly expressed in early oocytes. RNAi-mediated VgR silencing caused defective yolk granule biogenesis, leading to the accumulation of the main yolk protein precursors, Vg and RHBP, in the hemolymph, yet oviposition and fertilization proceeded normally. The resulting eggs were yolk-depleted and non-viable. Remarkably, VgR knockdown reduced bacterial 16S rRNA levels in oocytes while promoting the expansion of several members of the core virome, a phenotype not reproduced by Vg silencing. Neither purified Vg nor changes in immune (defensin) or RNA interference pathways explained the microbial shifts. These findings indicate that VgR governs not only yolk endocytosis but also the trafficking of microbial components into developing oocytes. We propose that VgR contributes to the linking of yolk endocytic dynamics and microbial homeostasis, influencing the balance of microbial components within developing oocytes. This connection broadens the functional scope of the VgR and provides new insight into how vertical transmission processes are shaped in this major Chagas disease vector. Author summaryEgg-laying animals must load their eggs with enough nutrients to support early development. In insects, this process depends on a receptor that brings yolk proteins into the growing egg. Here, we studied this receptor in Rhodnius prolixus, a major vector of Chagas disease, and uncovered an unexpected link between yolk uptake and the microorganisms that enter the egg. When we blocked the receptor, females continued to produce and lay eggs, but these eggs failed to accumulate yolk and could not support embryonic development. Strikingly, the absence of the receptor also shifted the microbial community inside the oocyte: bacterial levels dropped, while several viruses expanded. These changes did not result from differences in yolk proteins, immune activation, or direct antimicrobial effects, indicating that the receptor itself influences microbial entry or persistence in the egg. Our findings reveal that this yolk receptor plays a dual role, providing nutrients and shaping the microbial community that is passed from mother to offspring. This work highlights an unrecognized layer of interaction between reproduction and microbial transmission in an important disease vector, offering new perspectives for understanding and potentially disrupting vertical transmission pathways.

cell biology↗

TagF coordinates spike-loading as an intermediate checkpoint in Type VI Secretion System assembly

Diderm bacteria use contact-dependent Type VI secretion systems (T6SS) to gain a competitive advantage within bacterial communities and during infection. Whereas the structural core assembly of T6SS is well characterized, the role of diverse accessory proteins during assembly remains under investigation. One well-conserved accessory protein is TagF, a post-translational inhibitor of T6SS dynamics, which was previously characterized in the context of a kinase-phosphatase signaling relay. Here, we identify a subset of T6SS clusters in which TagF occurs in a distinct regulatory context and without known binding partners. Investigating the role of TagF in the constitutively active Acinetobacter baylyi T6SS, we show that though TagF can suppress assembly dynamics, it primarily acts as an assembly coordinator. Using structured illumination microscopy, we show that TagF coordinates the transition from baseplate assembly to sheath elongation by preventing premature and nonproductive sheath assembly in absence of the VgrG spike. Direct interactions with the conserved T6SS tube protein Hcp suggested that TagF blocks sheath elongation by binding and disrupting Hcp hexamers and thus preventing tube formation. Finally, we show that TagF activity depends on crosstalk with TagZ, a previously uncharacterized membrane-associated accessory protein that recruits TagF to the cell periphery, and demonstrate that this interaction can be specifically disrupted by expression of an artificial TagF-binding protein. Together, our findings establish a novel role of TagF as a checkpoint protein that controls for spike-insertion into the baseplate to ensure effective T6SS assembly.

microbiology↗

The Viral AlphaFold Database of monomers and homodimers reveals conserved protein folds in viruses of bacteria, archaea, and eukaryotes

Viruses are among the most abundant and genetically diverse entities on Earth, yet the functions and evolutionary origins of most viral proteins remain poorly understood. Their rapid evolution often obscures evolutionary relationships, making it difficult to assign functions using sequence-based methods alone. Although conservation of protein fold can reveal deep homologies undetectable by sequence comparison, viral proteins remain vastly underrepresented in structural databases, limiting our ability to explore them at the structural level. Here, we address this gap by clustering all unique viral sequences from the NCBI RefSeq database and predicting the structures of [~]27,000 representative proteins using AlphaFold2, creating a large-scale viral structural resource, the Viral AlphaFold Database (VAD). We uncover [~]10,000 proteins belonging to clusters that share folds across viruses infecting bacteria, archaea, and eukaryotes, revealing shared protein folds across diverse host-infecting viruses. We also predict oligomeric states using AlphaFold2-based homodimer modelling, alongside structural comparisons to the Protein Data Bank, providing valuable new data on the potential for viral proteins to oligomerise. We further reveal that large regions of the viral protein universe remain functionally dark and report the discovery and experimental validation of a previously uncharacterised antiviral toxin-antitoxin (TA) system. VAD is a resource that provides a foundation for exploring viral structure-function relationships, including ancient folds that shape viral interactions across all life. Predicted structures used in this study are available at data-sharing.atkinson-lab.com/vad/.

molecular biology↗

Music as a real-time fMRI neurofeedback interface for modulating interhemispheric connectivity: effects on mood and recruitment of the putamen and insula

Music is a universal language that transcends cultures and is deeply rooted in human evolutionary history. Its creation and appreciation recruit the limbic and reward systems, leading to the evocation of emotions ranging from happiness and sadness to tenderness and grief. Here, we investigate the potential of music as an interventional tool in a novel neurofeedback connectivity-based experiment. This study proposes a musical interface for real-time fMRI neurofeedback that is adaptable to diverse experimental paradigms, namely the ones aiming at improving mood and other affective dimensions. Using a previously developed motor imagery connectivity-based approach, we evaluate its feasibility and efficacy by comparing the modulation of bilateral premotor cortex (PMC) activity during functional runs with real versus sham (random) feedback in 22 healthy adults. We also assess its performance against a visual feedback interface. The experiment involves a 50-minute MRI session, including anatomical scans, a PMC functional localizer run, and four neurofeedback runs (two with active feedback and two with sham feedback). Pre- and post-session questionnaires assess the neurobehavioral impact on mood, musical background (as a potential predictor of NF success), and subjective feedback experiences. During neurofeedback, participants perform motor imagery of finger-tapping, with feedback delivered as a dynamic, pre-validated chord progression that evolves or regresses based on the functional connectivity between left and right PMC. We found that our implementation of music-based feedback was successful, with participants managing to modulate their own connectivity using the proposed interface. The modulation performance was similar for active and sham NF runs, possibly due to the power of music to boost neuromodulation, but the network recruitment was stronger for active NF, including in the insula, putamen, and target ROIs. Behaviorally, we found a decrease in tension and an improvement in the overall mood of the participants after the session. When comparing our results to previous NF data with a visual interface, we found stronger brain activations, in particular in NF-relevant regions such as the insula and the putamen. This work shows that it is possible to directly modulate interhemispheric connectivity using a rt-fMRI musical interface with direct effects on mood and recruitment of saliency and learning networks.

neuroscience↗

Diurnal dynamics of multilayer brain networks predict cognitive trajectories in aging

ObjectivesResting-state functional connectivity (rsFC) is a highly dynamic process that varies across different times of the day within each individual. Although this variability was long considered to be noise, recent evidence suggests it may allow for an optimal adaptation to changes in the environment. However, the way rsFC is shaped on a circadian scale and its association with cognition are still unclear. MethodsWe analyzed data from 90 late-middle-age participants from the Cognitive Fitness in Aging study (61 women; 50-69y). Participants completed five electroencephalographic (EEG) recordings of spontaneous resting-state activity spread over 20h of prolonged wakefulness. Using a temporal multilayer network approach, we characterized the diurnal variations of the dynamic recruitment and integration of resting-state brain networks. We focused on the theta and gamma frequency bands within the default mode network (DMN), central executive network (CEN), and salience network (SN). Additionally, we investigated the relationship recruitment and integration of these network with baseline cognitive performance and at 7-year longitudinal follow-up, as well as with positron emission tomography (PET) early neuropathological markers of Alzheimers disease such as {beta}-amyloid and tau/neuroinflammation. ResultsDiurnal changes in theta and gamma dynamics were associated with distinct cognitive aspects. Specifically, higher baseline memory performance was associated with higher theta dynamic integration of the SN and the CEN, as well as higher theta dynamic recruitment of the DMN. Moreover, lower longitudinal memory decline at 7-year was associated with higher theta dynamic integration of the SN, CEN, and DMN. In contrast, higher gamma diurnal dynamic integration of the SN and the CEN was associated with lower executive and attentional performance, as well as higher early {beta}-amyloid accumulation, at baseline. DiscussionThese findings suggest that maintaining a balance between network flexibility and stability throughout the diurnal phase of the circadian cycle may play a crucial role in cognitive aging, with stable theta-band connectivity supporting memory, whereas excessive gamma-band stability in the SN and CEN may contribute to executive decline and early amyloid accumulation. These insights highlight the importance of considering time-of-day in brain rsFC studies, calling for a temporal multilayer approach to capture these dynamic patterns more effectively.

neuroscience↗

Spatial profiling identifies regionally distinct microenvironments and targetable immunosuppressive mechanisms in pediatric osteosarcoma pulmonary metastases.

Osteosarcoma is the most common malignant bone tumor in young patients and remains a significant clinical challenge, particularly in the context of metastatic disease. Despite extensive documentation of genomic alterations in osteosarcoma, studies detailing the immunosuppressive mechanisms within the metastatic osteosarcoma microenvironment are lacking. Our objective was to characterize the spatial transcriptional landscape of metastatic osteosarcoma to reveal these immunosuppressive mechanisms and identify promising therapeutic targets. Here, we performed spatial transcriptional profiling on a cohort of osteosarcoma pulmonary metastases from pediatric patients. We reveal a conserved spatial gene expression pattern resembling a foreign body granuloma, characterized by peripheral inflammatory signaling, fibrocollagenous encapsulation, lymphocyte exclusion, and peritumoral macrophage accumulation. We also show that the intratumoral microenvironment of these lesions lack inflammatory signaling. Additionally, we identified CXCR4 as an actionable immunomodulatory target that bridges both the intratumoral and extratumoral microenvironments and highlights the spatial heterogeneity and complexity of this pathway. Collectively, this study reveals that metastatic osteosarcoma specimens are comprised of multiple regionally distinct immunosuppressive microenvironments.

cancer biology↗

Heat Stress on the brown Seaweed Ascophyllum nodosum: differential population sensitivity to future climate.

Accurate forecasts of the biological impacts of climate change require a better understanding of how small-scale temperature variability affects individual physiology and population dynamics. But doing so for intertidal species with large distribution ranges, while also accounting for the effect of local adaptation, presents numerous technical challenges. Here, we assessed the macroecological consequences of thermal stress on the cold-adapted brown seaweed Ascophyllum nodosum across its European distribution. We collected specimens from ten populations spanning latitudes 41{degrees}N to 60{degrees}N and subjected them to simulated intertidal heat stress using a novel, custom-built experimental setup that replicated realistic conditions, including tidal cycles, light conditions, and temperature trajectories based on in situ data. Our factorial design comprised eight experimental treatments, combining two high-tide water temperatures (15 {degrees}C and 20.5 {degrees}C) with four low-tide peak temperatures (28.5 {degrees}C to 40.5 {degrees}C). Physiological performance was evaluated through measurements of growth, mortality, and oxygen production. Results indicate that thermal stress is more closely associated with the magnitude of temperature change between high and low tides rather than the absolute maximum temperatures reached. Algae exposed to warmer water temperatures (20.5 {degrees}C) consistently outperformed those in colder water (15 {degrees}C), suggesting that cold upwelled waters at the species southern limit may not be essential for survival. Southern populations demonstrated higher resilience to thermal stress than central and northern counterparts. Integrating these physiological responses with climate projections, we employed demographic models to forecast long-term population dynamics. The models predict that future climatic conditions could exceed the thermal resilience of specific populations, leading to uneven impacts across the European distribution of the species. Notwithstanding, range contractions may occur at the warm edge of the distribution, where populations, though more resilient to thermal stress, could still be overwhelmed by the pace of warming. This study underscores the importance of realistic experimental simulations in evaluating species thermal tolerance and highlights the potential for climate change to differentially impact populations along large latitudinal gradients.

ecology↗

Structural implications of BK polyomavirus sequence variations in the major viral capsid protein Vp1 and large T-antigen: a computational study

BK polyomavirus (BKPyV) is a double-stranded DNA virus causing nephropathy, hemorrhagic cystitis, and urothelial cancer in transplant patients. The BKPyV-encoded capsid protein Vp1 and large T-antigen (LTag) are key targets of neutralizing antibodies and cytotoxic T-cells, respectively. Our single-center data suggested that variability in Vp1 and LTag may contribute to failing BKPyV-specific immune control, and impact vaccine design. We therefore analyzed all available entries in GenBank (1516 VP1; 742 LTAG) and explored potential structural effects using computational approaches. BKPyV-genotype (gt)1 was found in 71.18% of entries, followed by BKPyV-gt4 (19.26%), BKPyV-gt2 (8.11%) and BKPyV-gt3 (1.45%), but rates differed according to country and specimen type. Vp1-mutations matched a serotype different than the assigned one or were serotype-independent in 43%, 18% affected more than one amino acid. Notable Vp1-mutations altered antibody-binding domains, interactions with sialic acid receptors, or were predicted to change conformation. LTag-sequences were more conserved, with only 16 mutations detectable in more than one entry and without significant effects on LTag-structure or interaction domains. However, LTag changes were predicted to affect HLA-class I presentation of immunodominant 9mers to cytotoxic T-cells. These global data strengthen single center observations and specifically our earlier findings revealing mutant 9mer epitopes conferring immune escape from HLA-I cytotoxic T cells. We conclude that variability of BKPyV-Vp1 and LTag may have important implications for diagnostic assays assessing BKPyV-specific immune control and for vaccine design. IMPORTANCEType and rate of amino acid variations in BKPyV may provide important insights into BKPyV diversity in human populations and an important step towards defining determinants of BKPyV-specific immunity needed to protect vulnerable patients from BKPyV diseases. Our analysis of BKPyV sequences obtained from human specimens reveals an unexpectedly high genetic variability for this double-stranded DNA virus that strongly relies on host cell DNA replication machinery with its proof reading and error correction mechanisms. BKPyV variability and immune escape should be taken into account when designing further approaches to antivirals, monoclonal antibodies and vaccines for patients at risk of BKPyV diseases.

microbiology↗

Spatiotemporal dynamics of cytokines expression dictate fetal liver hematopoiesis.

During embryogenesis, yolk-sac and intra-embryonic-derived hematopoietic progenitors, comprising the precursors of adult hematopoietic stem cells, converge into the fetal liver. With a new staining strategy, we defined all non-hematopoietic components of the fetal liver and found that hepatoblasts are the major producers of hematopoietic growth factors. We identified mesothelial cells, a novel component of the stromal compartment, producing Kit ligand, a major hematopoietic cytokine. A high-definition imaging dataset analyzed using a deep-learning based pipeline allowed the unambiguous identification of hematopoietic and stromal populations, and enabled determining a neighboring network composition, at the single cell resolution. Throughout active hematopoiesis, progenitors preferentially associate with hepatoblasts, but not with stellate or endothelial cells. We found that, unlike yolk sac-derived progenitors, intra-embryonic progenitors respond to a chemokine gradient created by CXCL12-producing stellate cells. These results revealed that FL hematopoiesis is a spatiotemporal dynamic process, defined by an environment characterized by low cytokine concentrations.

developmental biology↗

What is hidden in the darkness? Deep-learning assisted large-scale protein family curation uncovers novel protein families and folds

Driven by the development and upscaling of fast genome sequencing and assembly pipelines, the number of protein-coding sequences deposited in public protein sequence databases is increasing exponentially. Recently, the dramatic success of deep learning-based approaches applied to protein structure prediction has done the same for protein structures. We are now entering a new era in protein sequence and structure annotation, with hundreds of millions of predicted protein structures made available through the AlphaFold database. These models cover most of the catalogued natural proteins, including those difficult to annotate for function or putative biological role based on standard, homology-based approaches. In this work, we quantified how much of such "dark matter" of the natural protein universe was structurally illuminated by AlphaFold2 and modelled this diversity as an interactive sequence similarity network that can be navigated at https://uniprot3d.org/atlas/AFDB90v4. In the process, we discovered multiple novel protein families by searching for novelties from sequence, structure, and semantic perspectives. We added a number of them to Pfam, and experimentally demonstrate that one of these belongs to a novel superfamily of translation-targeting toxin-antitoxin systems, TumE-TumA. This work highlights the role of large-scale, evolution-driven protein comparison efforts in combination with structural similarities, genomic context conservation, and deep-learning based function prediction tools for the identification of novel protein families, aiding not only annotation and classification efforts but also the curation and prioritisation of target proteins for experimental characterisation.

bioinformatics↗

Embedding-based alignment: combining protein language models and alignment approaches to detect structural similarities in the twilight-zone

Language models are now routinely used for text classification and generative tasks. Recently, the same architectures were applied to protein sequences, unlocking powerful tools in the bioinformatics field. Protein language models (pLMs) generate high dimensional embeddings on a per-residue level and encode the "semantic meaning" of each individual amino acid in the context of the full protein sequence. Multiple works use these representations as a starting point for downstream learning tasks and, more recently, for identifying distant homologous relationships between proteins. In this work, we introduce a new method that generates embedding-based protein sequence alignments (EBA), and show how these capture structural similarities even in the twilight zone, outperforming both classical sequence-based scores and other approaches based on protein language models. The method shows excellent accuracy despite the absence of training and parameter optimization. We expect that the association of pLMs and alignment methods will soon rise in popularity, helping the detection of relationships between proteins in the twilight-zone.

bioinformatics↗

What is hidden in the darkness? Characterization of AlphaFold structural space.

The recent public release of the latest version of the AlphaFold database has given us access to over 200 million predicted protein structures. We use a "shape-mer" approach, a structural fragmentation method analogous to sequence k-mers, to describe these structures and look for novelties - both in terms of proteins with rare or novel structural composition and possible functional annotation of under-studied proteins. Data and code will be made available at https://github.com/TurtleTools/afdb-shapemer-darkness

bioinformatics↗