Biology subjects

Wood, S. J.

Publications and source records attributed to Wood, S. J..

4 recordsLinked to original sources

bioRxiv2022

Artificial Gravity During a Spaceflight Analog Alters Brain Sensory Connectivity

Spaceflight has numerous untoward effects on human physiology. Various countermeasures are under investigation including artificial gravity (AG). Here, we investigated whether AG alters resting-state brain functional connectivity changes during head-down tilt bed rest (HDBR), a spaceflight analog. Participants underwent 60 days of HDBR. Two groups received daily AG administered either continuously (cAG) or intermittently (iAG). A control group received no AG. We assessed resting-state functional connectivity before, during, and after HDBR. We also measured balance and mobility changes from pre-to post-HDBR. We examined how functional connectivity changes throughout HDBR and whether AG is associated with differential effects. We found differential connectivity changes by group between posterior parietal cortex and multiple somatosensory regions. The control group exhibited increased functional connectivity between these regions throughout HDBR whereas the cAG group showed decreased functional connectivity. This finding suggests that AG alters somatosensory reweighting during HDBR. We also observed brain-behavioral correlations that differed significantly by group. Control group participants who showed increased connectivity between the putamen and somatosensory cortex exhibited greater mobility declines post-HDBR. For the cAG group, increased connectivity between these regions was associated with little to no mobility declines post-HDBR. This suggests that when somatosensory stimulation is provided via AG, functional connectivity increases between the putamen and somatosensory cortex are compensatory in nature, resulting in reduced mobility declines. Given these findings, AG may be an effective countermeasure for the reduced somatosensory stimulation that occurs in both microgravity and HDBR.

neuroscience↗

bioRxiv2022

Impacts of Spaceflight Experience on Human Brain Structure

Spaceflight induces widespread changes in human brain morphology. It is unclear if these brain changes differ with varying mission durations or ones history of spaceflight experience (e.g., number of prior missions, time between missions). Here we addressed this issue by quantifying voxelwise post-flight changes in gray matter volume, white matter microstructure, extracellular free water (FW), and ventricular volume in a sample of 28 astronauts. We found that longer missions induced greater ventricular expansion and larger FW displacement at the top of the brain. A greater number of prior missions was associated with white matter microstructure declines in a tract supporting voluntary leg movement. Longer inter-mission intervals were associated with greater ventricle expansion, with compensatory ventricular expansion observed only in those crewmembers with inter-missions intervals of 3 years or longer. Longer missions therefore induce more extensive brain fluid shifts, and the ventricles may require at least 3 years to recover post-flight.

neuroscience↗

bioRxiv2021

Overriding defective FPR chemotaxis signaling in diabetic neutrophil stimulates infection control in diabetic wound

Infection is a major co-morbidity that contributes to impaired healing in diabetic wounds. Although impairments in diabetic neutrophils have been blamed for this co-morbidity, what causes these impairments and whether they can be overcome, remain largely unclear. Diabetic neutrophils, extracted from diabetic individuals, exhibit chemotaxis impairment but this peculiar functional impairment has been largely ignored because it appears to contradict the clinical findings which blame excessive neutrophil influx (neutrophilia) as a major impediment to healing in chronic diabetic ulcers. Here, we report that exposure to glucose in diabetic range results in impaired chemotaxis signaling through the FPR1 chemokine receptor in neutrophils, culminating in reduced chemotaxis and delayed neutrophil trafficking in wound in diabetic animals, and rendering diabetic wound vulnerable to infection. We further show that at least some auxiliary chemokine receptors remain functional under diabetic conditions and their engagement by the pro-inflammatory cytokine CCL3, overrides the requirement for FPR1 signaling and substantially improves infection control by jumpstarting the neutrophil response toward infection, and stimulates healing in diabetic wound. We posit that CCL3 may have real therapeutic potential for the treatment of diabetic foot ulcers if it is applied topically after the surgical debridement process which is intended to reset chronic ulcers into acute fresh wounds.

immunology↗

bioRxiv2019

Entropy of a bacterial stress response is a generalizable predictor for fitness and antibiotic sensitivity.

Genes implicated in bacterial stress responses have been used to construct models that infer the growth outcome of a bacterium in the presence of antibiotics with the objective to develop novel diagnostic methods in the clinic. Current models are trained on data specific to a species or type of stress, making them potentially limited in their application. It is unclear if a generalizable response-signature exists that can predict bacterial fitness independent of strain, species or type of stress. Here we present a substantial RNA-Seq and experimental evolution dataset for 9 strains and species, under multiple antibiotic and non-antibiotic stress conditions. We show that gene panel-based models can accurately predict antibiotic mechanism of action, as well as the fitness outcome of Streptococcus pneumoniae in the presence of antibiotics or under nutrient depletion. However, these models quickly become species-specific as gene homology is limited. Instead, we define a new concept, transcriptomic entropy, which we use to quantify the amount of transcriptional disruption that occurs in a bacterium when responding to the environment. With entropy at the center, we train a suite of predictive (machine learning) models enabling generalizable fitness and antibiotic sensitivity predictions. These entropy-based models that predict bacterial fitness are validated for 7 Gram-positive and -negative species under antibiotic and non-antibiotic conditions indicating that transcriptomic entropy can be used as a generalizable stress signature. Moreover, rather than being a binary indicator of fitness, an entropy-based model was developed and validated to predict the minimum inhibitory concentration of an antibiotic. Lastly, we show that the inclusion of a varied-set of multi-omics features of a bacterial stress response further enhances fitness predictions by reducing ambiguity. By demonstrating the feasibility of generalizable predictions of bacterial fitness, this work establishes the fundamentals for potentially new approaches in infectious disease diagnostics, including antibiotic susceptibility testing.\n\nSignificance statementAccurate predictions of bacterial fitness outcome could potentially have clinical diagnostic value, such as predicting optimum antibiotic choice and dosage for treating infectious diseases. Existing models of fitness predictions rely mainly on gene panel approaches, which may be species- and stress-specific due to a lack of gene and response conservation. In order to overcome this limitation, we generated a substantial experimental dataset and identified entropy as a universal stress response signature that quantifies the level of transcriptional disruption that is indicative of fitness outcome under a stressful condition. We present and validate for Gram-positive and negative species a suite of entropy-based models that enable accurate predictions of fitness outcome and the level of antibiotic sensitivity in a species and stress-type independent manner.

systems biology↗