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Severe infections are a major stress on haematopoiesis, where the consequences for haematopoietic stem cells (HSCs) have only recently started to emerge. HSC function critically depends on the integrity of complex bone marrow (BM) niches; however, what role the BM microenvironment plays in mediating the effects of infection on HSCs remains an open question. Here, using a murine model of malaria and combining single-cell RNA sequencing, mathematical modelling, transplantation assays and intravital microscopy, we show that haematopoiesis is reprogrammed upon infection, whereby the HSC compartment turns over substantially faster than at steady-state and HSC function is drastically affected. Interferon is found to affect both haematopoietic and mesenchymal BM cells and we specifically identify a dramatic loss of osteoblasts and alterations in endothelial cell function. Osteo-active parathyroid hormone treatment abolishes infection-triggered HSC proliferation and—coupled with reactive oxygen species quenching—enables partial rescuing of HSC function.Haltalli et al. show that Plasmodium berghei infection induces interferon release, and affects haematopoietic stem cell proliferation and function, as well as osteoblasts and vascular integrity, in the bone marrow niche.

Interactions between viruses during coinfections can influence viral fitness and population diversity, as seen in the generation of reassortant pandemic influenza A virus (IAV) strains. However, opportunities for interactions between closely related viruses are limited by a process known as superinfection exclusion (SIE), which blocks coinfection shortly after primary infection. Using IAVs, we asked whether SIE, an effect which occurs at the level of individual cells, could limit interactions between populations of viruses as they spread across multiple cells within a host. To address this, we first measured the kinetics of SIE in individual cells by infecting them sequentially with 2 isogenic IAVs, each encoding a different fluorophore. By varying the interval between addition of the 2 IAVs, we showed that early in infection SIE does not prevent coinfection, but that after this initial lag phase the potential for coinfection decreases exponentially. We then asked how the kinetics of SIE onset controlled coinfections as IAVs spread asynchronously across monolayers of cells. We observed that viruses at individual coinfected foci continued to coinfect cells as they spread, because all new infections were of cells that had not yet established SIE. In contrast, viruses spreading towards each other from separately infected foci could only establish minimal regions of coinfection before reaching cells where coinfection was blocked. This created a pattern of separate foci of infection, which was recapitulated in the lungs of infected mice, and which is likely to be applicable to many other viruses that induce SIE. We conclude that the kinetics of SIE onset segregate spreading viral infections into discrete regions, within which interactions between virus populations can occur freely, and between which they are blocked.

Single molecule fluorescence in situ hybridisation (smFISH) has become a valuable tool to investigate the mRNA expression of single cells. However, it requires a considerable amount of programming expertise to use currently available open-source analytical software packages to extract and analyse quantitative data about transcript expression. Here, we present FISHtoFigure, a new software tool developed specifically for the analysis of mRNA abundance and co-expression in QuPath-quantified, multi-labelled smFISH data. FISHtoFigure facilitates the automated spatial analysis of transcripts of interest, allowing users to analyse populations of cells positive for specific combinations of mRNA targets without the need for computational image analysis expertise. As a proof of concept and to demonstrate the capabilities of this new research tool, we have validated FISHtoFigure in multiple biological systems. We used FISHtoFigure to identify an upregulation in the expression of Cd4 by T-cells in the spleens of mice infected with influenza A virus, before analysing more complex data showing crosstalk between microglia and regulatory B-cells in the brains of mice infected with Trypanosoma brucei brucei . These analyses demonstrate the ease of analysing cell expression profiles using FISHtoFigure and the value of this new tool in the field of smFISH data analysis.

Interactions between viruses during coinfections can influence viral fitness and population diversity, as seen in the generation of reassortant pandemic influenza A virus (IAV) strains. However, opportunities for interactions between closely related viruses are limited by a process known as superinfection exclusion (SIE), which blocks coinfection shortly after primary infection. Using IAVs, we asked whether SIE, an effect which occurs at the level of individual cells, could limit interactions between populations of viruses as they spread across multiple cells within a host. To address this, we first measured the kinetics of SIE in individual cells by infecting them sequentially with 2 isogenic IAVs, each encoding a different fluorophore. By varying the interval between addition of the 2 IAVs, we showed that early in infection SIE does not prevent coinfection, but that after this initial lag phase the potential for coinfection decreases exponentially. We then asked how the kinetics of SIE onset controlled coinfections as IAVs spread asynchronously across monolayers of cells. We observed that viruses at individual coinfected foci continued to coinfect cells as they spread, because all new infections were of cells that had not yet established SIE. In contrast, viruses spreading towards each other from separately infected foci could only establish minimal regions of coinfection before reaching cells where coinfection was blocked. This created a pattern of separate foci of infection, which was recapitulated in the lungs of infected mice, and which is likely to be applicable to many other viruses that induce SIE. We conclude that the kinetics of SIE onset segregate spreading viral infections into discrete regions, within which interactions between virus populations can occur freely, and between which they are blocked. Once a virus has infected a cell it begins to exclude other, related viruses. This study shows that this process compartmentalizes influenza viruses into distinct regions as they spread within their host, reducing the opportunities for viral genetic exchange.

Single molecule fluorescence in situ hybridisation (smFISH) has become a valuable tool to investigate the mRNA expression of single cells. However, it requires a considerable amount of bioinformatic expertise to use currently available open-source analytical software packages to extract and analyse quantitative data about transcript expression. Here, we present FISHtoFigure, a new software tool developed specifically for the analysis of mRNA abundance and co-expression in QuPath-quantified, multi-labelled smFISH data. FISHtoFigure facilitates the automated spatial analysis of transcripts of interest, allowing users to analyse populations of cells positive for specific combinations of mRNA targets without the need for bioinformatics expertise. As a proof of concept and to demonstrate the capabilities of this new research tool, we have validated FISHtoFigure in multiple biological systems. We used FISHtoFigure to identify an upregulation of T-cells in the spleens of mice infected with influenza A virus, before analysing more complex data showing crosstalk between microglia and regulatory B-cells in the brains of mice infected with Trypanosoma brucei brucei. These analyses demonstrate the ease of analysing cell expression profiles using FISHtoFigure and the value of this new tool in the field of smFISH data analysis.

Influenza A virus (IAV) infection leads to the formation of mucosal memory CD4 T cells that can protect the host. An in-depth understanding of the signals that shape memory cell development is required for more effective vaccine design. We have examined the formation of memory CD4 T cells in the lung following IAV infection of mice, characterising changes to the lung architecture and immune cell composition. IAV-specific CD4 T cells were found throughout the lung at both primary and memory time points. These cells were found near lung airways and in close contact with a range of immune cells including macrophages, dendritic cells, and B cells. Interactions between lung IAV-specific CD4 T cells and MHCII+ cells during the primary immune response were important in shaping the subsequent memory pool. Treatment with an anti-MHCII blocking antibody increased the proportion of memory CD4 T cells found at lung airways but reduced interferon-gamma expression by IAV-specific immunodominant memory CD4 T cells. The immunodominant CD4 T cells expressed higher levels of PD1 than other IAV-specific CD4 T cells and PD1+ memory CD4 T cells were located further away from MHCII+ cells than their PD1-negative counterparts. This distinction in location was lost in mice treated with anti-MHCII antibody. These data suggest that sustained antigen presentation in the lung impacts on the formation of memory CD4 T cells by regulating their cytokine production and location.Competing Interest StatementThe authors have declared no competing interest.Footnotes* Small changes to figure 1 to add additional H&E staining and some small corrections of the text.

Influenza viruses can interact during coinfections, allowing viral fitness to be altered by genome complementation and competition, and increasing population diversity through reassortment. However, opportunities for these interactions are limited, as coinfection is blocked shortly after primary infection by a process known as superinfection exclusion (SIE). We asked whether SIE, which occurs at the level of individual cells, could limit within-host interactions between populations of influenza viruses as they spread across regions of cells. We first created a simplified model of within-host spread by infecting monolayers of cells with two isogenic influenza A viruses, each encoding a different fluorophore, and measuring the proportion of coinfected cells. In this system SIE begins within 2-4 hours of primary infection, with the kinetics of onset defined by the dose of primary virus. We then asked how SIE controls opportunities for coinfection as viruses spread across a monolayer of cells. We observed that viruses spreading from a single coinfected focus continued to coinfect cells as they spread, as all new infections were of cells that had not yet established SIE. In contrast, viruses spreading towards each other from separately infected foci could only establish minimal regions of coinfection before SIE blocked further coinfection. This patterning was recapitulated in the lungs of infected mice and is likely to apply to other viruses that exhibit SIE. It suggests that the kinetics of SIE onset separate a spreading infection into discrete regions, within which interactions between virus populations can occur freely, and between which they are blocked. Viral fitness and diversity are altered by genome interactions, which occur when multiple viruses coinfect a cell. This has been extensively studied for influenza A viruses (IAV), which use genome reassortment to adapt to new hosts and create pandemic strains, and whose replication can be compromised by the acquisition of defective-interfering RNAs. Coinfection of an individual cell by IAV is restricted by the gradual onset of superinfection exclusion (SIE). Replication of IAVs within host organisms involve the asynchronous replication of viruses as they spread to infect multiple cells. We found that under these circumstances, SIE creates spatially separated sub-populations of IAV, between which there are limited opportunities for genome interactions. Our work suggests SIE will cause many viruses to segregate into distinct subpopulations within their hosts, constraining the effects of genome interactions on their fitness and evolution.

Abstract Acute myeloid leukemia (AML) is a blood cancer of the myeloid lineage. Its prognosis remains poor, highlighting the need for new therapeutic and precision medicine approaches. AML symptoms often include cytopenias, linked to loss of healthy hematopoietic stem and progenitor cells (HSPCs). The mechanism behind HSPC decline is complex and still poorly understood. Here, intravital microscopy (IVM) of a well-established experimental model of AML allows direct observation of the interactions between healthy and malignant cells in the bone marrow (BM), suggesting that physical dislodgment of healthy cells by AML through damaged vasculature may play an important role. Numerous human leukemia types, particularly MLL-AF9 samples, show high expression levels of multiple matrix metalloproteinases (MMPs). Therefore, we evaluate the therapeutic potential of the MMP inhibitor (MMPI) prinomastat. IVM analyses of treated mice reveal reduced vascular permeability and healthy cell clusters in circulation, and lower AML cell speed. Furthermore, treated mice have decreased BM infiltration, increased retention of healthy HSPCs in the BM and increased survival following chemotherapy. Overall, our results suggest that MMPIs could be a promising complementary therapy to reduce AML growth and limit the loss of HSPC and BM vascular damage caused by MLL-AF9 and possibly other AML subtypes. Competing Interest Statement The authors have declared no competing interest. Footnotes * The authors have declared that no conflict of interest exists.

Background Hypoxic-ischemic encephalopathy (HIE) is a leading cause of neonatal mortality and morbidity, yet no validated biomarkers currently exist to predict long-term outcomes. We investigated the potential of the neonatal urinary metabolomic profile as a predictor of long-term neurodevelopmental outcomes in HIE newborns treated with therapeutic hypothermia (TH). Methods We conducted a longitudinal study in neonates with HIE undergoing TH. Urine samples collected during TH were analyzed using untargeted metabolomics via mass spectrometry. Based on long-term follow-up outcomes, patients were categorized into two groups: the adverse outcome (AO) group, defined by perinatal death, cerebral palsy, and/or an intelligence quotient (IQ) < 70, and the favourable outcome (FO) group, defined as absence of CP and IQ ≥ 70. Additionally, we assessed the predictive value of early neonatal brain magnetic resonance imaging (MRI) in relation to the aforementioned outcomes. Results Among 53 newborns treated with TH for HIE, long-term follow-up outcomes were available for 40; 29 were classified as FO and 11 as AO group. To mitigate bias, 11 FO patients were matched with 11 AO patients based on similar perinatal characteristics. Metabolomic analysis identified 21 metabolites distinguishing the two groups, with γ-butyrolactone, N -acetyl-galactosamine/glucosamine, Aldosterone, and Creatinine showing independent discriminative capability among groups. Brain MRI demonstrated a 67% positive and 96% negative predictive value for adverse outcomes. Conclusions The identified metabolites are implicated in neuromodulation and neuronal susceptibility to damage, suggesting their potential as prognostic markers for long-term outcomes in HIE and warranting further investigation. This is the first study linking the acute-phase metabolomic profile with long-term neurodevelopmental outcomes in HIE neonates, supporting its prognostic potential.

We performed a retrospective immunological analysis of the antibody response in serum and in nasopharyngeal swabs (NPS) obtained from 46 individuals infected with ancestral SARS-CoV-2 Wuhan-Hu-1 strain during the first COVID-19 wave in Cagliari (Sardinia, Italy), with a 4-month follow-up after the hospital admission. We implemented a comprehensive antibody response in serum and in mucosal samples using assays established in our laboratories. In NPS we evaluated the viral load by real time PCR, presence and kinetics of anti-Spike IgG and IgA by ELISA as well as their anti-Wuhan neutralization activity, showing induction and persistence of anti-viral immunity at the mucosal level. Neutralizing antibodies were measured in serum and NPS using a safe pseudovirus-based assay validated after comparison with a standard neutralization test using live SARS-CoV-2. We evaluated cross-neutralizing antibodies against all the major early variants of concerns (VoC) in sera. Of note, we detected a remarkable reduction of neutralizing activity against BA.1 compared to BA.2 and BA.5 Omicron subvariants, which was confirmed in sera from an analogous cohort of patients at the San Raffaele hospital in Milan, a geographically distant region of Italy, infected with the ancestral virus during the same period of time.