Myo-inositol Levels in the Dorsal Anterior Cingulate Cortex Predicts Anxiety-to-Eat in Anorexia Nervosa.

Background: Anorexia nervosa (AN) is a mental and behavioral health condition characterized by an intense fear of weight or fat gain, severe restriction of food intake resulting in low body weight, and distorted self-perception of body shape or weight. While substantial research has focused on general anxiety in AN, less is known about eating-related anxiety and its underlying neural mechanisms. Therefore, we sought to characterize anxiety-to-eat in AN and examine the neurometabolic profile within the dorsal anterior cingulate cortex (dACC), a brain region putatively involved in magnifying the threat response. Methods: Women seeking inpatient treatment for AN and women of healthy weight without a lifetime history of an eating disorder (healthy controls; HC) completed a computer-based behavioral task assessing anxiety-to-eat in response to images of higher (HED) and lower (LED) energy density foods. Participants also underwent magnetic resonance spectroscopy of the dACC in a 3 Tesla scanner. Results: The AN group reported greater anxiety to eat HED and LED foods relative to the HC group. Both groups reported greater anxiety to eat HED foods relative to LED foods. The neurometabolite myo-inositol (mI) was lower in the dACC in AN relative to HC, and mI levels negatively predicted anxiety to eat HED but not LED foods in the AN group only. mI levels in the dACC were independent of body weight, body mass, and general anxiety. Conclusions: These findings provide critical new insight into the clinically challenging feature and underlying neural mechanisms of eating-related anxiety and indicate mI levels in the dACC could serve as a novel biomarker of illness severity that is independent of body weight to identify individuals vulnerable to disordered eating or eating pathology as well as a potential therapeutic target.

GABA-edited MEGA-PRESS at 3 T: Does a measured macromolecule background improve linear combination modeling?

PURPOSE: The J-difference edited γ-aminobutyric acid (GABA) signal is contaminated by other co-edited signals-the largest of which originates from co-edited macromolecules (MMs)-and is consequently often reported as "GABA+." MM signals are broader and less well-characterized than the metabolites, and are commonly approximated using a Gaussian model parameterization. Experimentally measured MM signals are a consensus-recommended alternative to parameterized modeling; however, they are relatively under-studied in the context of edited MRS. METHODS: To address this limitation in the literature, we have acquired GABA-edited MEGA-PRESS data with pre-inversion to null metabolite signals in 13 healthy controls. An experimental MM basis function was derived from the mean across subjects. We further derived a new parameterization of the MM signals from the experimental data, using multiple Gaussians to accurately represent their observed asymmetry. The previous single-Gaussian parameterization, mean experimental MM spectrum and new multi-Gaussian parameterization were compared in a three-way analysis of a public MEGA-PRESS dataset of 61 healthy participants. RESULTS: Both the experimental MMs and the multi-Gaussian parameterization exhibited reduced fit residuals compared to the single-Gaussian approach (p = 0.034 and p = 0.031, respectively), suggesting they better represent the underlying data than the single-Gaussian parameterization. Furthermore, both experimentally derived models estimated larger MM fractional contribution to the GABA+ signal for the experimental MMs (58%) and multi-Gaussian parameterization (58%), compared to the single-Gaussian approach (50%). CONCLUSIONS: Our results indicate that single-Gaussian parameterization of edited MM signals is insufficient and that both experimentally derived GABA+ spectra and their parameterized replicas improve the modeling of GABA+ spectra.

Identification of active main metabolites of anti-infective inhibitors of the macrophage infectivity potentiator protein by liquid chromatography using mass detection.

Due to increasing antibiotic resistance, the development of anti-infectives with new mechanisms of action is crucial. Virulence factors such as the "macrophage infectivity potentiator" (Mip) protein, which catalyzes the folding of proline-containing proteins by means of their cis-trans isomerase (PPIase) activity, have come into focus as a potential new target. Since the inhibition of Mip by small molecules has been shown to lead to reduced virulence and survival in vitro, especially of Gram-negative bacteria such as Burkholderia pseudomallei (Bp), Neisseria meningitidis (Nm), and Neisseria gonorrhoeae (Ng), or Coxiella burnetii (Cb), among many others, a library of Mip inhibitors was developed. As drug metabolism has a significant impact on the overall therapeutic outcome, this report describes the biotransformation of the most potent Mip inhibitors. Therefore, the anti-infectives were treated using human liver microsomes in vitro. Liquid chromatography with tandem mass spectrometry (LC/MS-MS) methods were applied to identify the metabolites and quantify the metabolic degradation of the hit compounds. Active metabolites, N-oxides, were found, leading to new opportunities for further drug development.

Integrated Short-TE and Hadamard-edited Multi-Sequence (ISTHMUS) for Advanced MRS.

Background: To examine data quality and reproducibility using ISTHMUS, which has been implemented as the standardized MR spectroscopy sequence for the multi-site Healthy Brain and Child Development (HBCD) study. Methods: ISTHMUS is the consecutive acquisition of short-TE PRESS (32 transients) and long-TE HERCULES (224 transients) data with dual-TE water reference scans. Voxels were positioned in the centrum semiovale, dorsal anterior cingulate cortex, posterior cingulate cortex and bilateral thalamus regions. After acquisition, ISTHMUS data were separated into the PRESS and HERCULES portions for analysis and modeled separately using Osprey. In vivo experiments were performed in 10 healthy volunteers (6 female; 29.5±6.6 years). Each volunteer underwent two scans on the same day. Differences in metabolite measurements were examined. T2 correction based on the dual-TE water integrals were compared with: 1) T2 correction based the default white matter and gray matter T2 reference values in Osprey; 2) shorter WM and GM T2 values from recent literature; and 3) reduced CSF fractions. Results: No significant difference in linewidth was observed between PRESS and HERCULES. Bilateral thalamus spectra had produced significantly higher (p<0.001) linewidth compared to the other three regions. Linewidth measurements were similar between scans, with scan-to-scan differences under 1 Hz for most subjects. Paired t-tests indicated a significant difference only in PRESS NAAG between the two thalamus scans (p=0.002). T2 correction based on shorter T2 values showed better agreement to the dual-TE water integral ratio. Conclusions: ISTHMUS facilitated and standardized acquisition and post-processing and reduced operator workload to eliminate potential human error.

Metabolite T1 relaxation times decrease across the adult lifespan.

Relaxation correction is an integral step in quantifying brain metabolite concentrations measured by in vivo magnetic resonance spectroscopy (MRS). While most quantification routines assume constant T1 relaxation across age, it is possible that aging alters T1 relaxation rates, as is seen for T2 relaxation. Here, we investigate the age dependence of metabolite T1 relaxation times at 3 T in both gray- and white-matter-rich voxels using publicly available metabolite and metabolite-nulled (single inversion recovery TI = 600 ms) spectra acquired at 3 T using Point RESolved Spectroscopy (PRESS) localization. Data were acquired from voxels in the posterior cingulate cortex (PCC) and centrum semiovale (CSO) in 102 healthy volunteers across 5 decades of life (aged 20-69 years). All spectra were analyzed in Osprey v.2.4.0. To estimate T1 relaxation times for total N-acetyl aspartate at 2.0 ppm (tNAA2.0) and total creatine at 3.0 ppm (tCr3.0), the ratio of modeled metabolite residual amplitudes in the metabolite-nulled spectrum to the full metabolite signal was calculated using the single-inversion-recovery signal equation. Correlations between T1 and subject age were evaluated. Spearman correlations revealed that estimated T1 relaxation times of tNAA2.0 (rs = -0.27; p < 0.006) and tCr3.0 (rs = -0.40; p < 0.001) decreased significantly with age in white-matter-rich CSO, and less steeply for tNAA2.0 (rs = -0.228; p = 0.005) and (not significantly for) tCr3.0 (rs = -0.13; p = 0.196) in graymatter-rich PCC. The analysis harnessed a large publicly available cross-sectional dataset to test an important hypothesis, that metabolite T1 relaxation times change with age. This preliminary study stresses the importance of further work to measure age-normed metabolite T1 relaxation times for accurate quantification of metabolite levels in studies of aging.

Model-based frequency-and-phase correction of 1H MRS data with 2D linear-combination modeling.

Purpose: Retrospective frequency-and-phase correction (FPC) methods attempt to remove frequency-and-phase variations between transients to improve the quality of the averaged MR spectrum. However, traditional FPC methods like spectral registration struggle at low SNR. Here, we propose a method that directly integrates FPC into a two-dimensional linear-combination model (2D-LCM) of individual transients ('model-based FPC'). We investigated how model-based FPC performs compared to the traditional approach, i.e., spectral registration followed by 1D-LCM in estimating frequency-and-phase drifts and, consequentially, metabolite level estimates. Methods: We created synthetic in-vivo-like 64-transient short-TE sLASER datasets with 100 noise realizations at 5 SNR levels and added randomly sampled frequency and phase variations. We then used this synthetic dataset to compare the performance of 2D-LCM with the traditional approach (spectral registration, averaging, then 1D-LCM). Outcome measures were the frequency/phase/amplitude errors, the standard deviation of those ground-truth errors, and amplitude Cramér Rao Lower Bounds (CRLBs). We further tested the proposed method on publicly available in-vivo short-TE PRESS data. Results: 2D-LCM estimates (and accounts for) frequency-and-phase variations directly from uncorrected data with equivalent or better fidelity than the conventional approach. Furthermore, 2D-LCM metabolite amplitude estimates were at least as accurate, precise, and certain as the conventionally derived estimates. 2D-LCM estimation of frequency and phase correction and amplitudes performed substantially better at low-to-very-low SNR. Conclusion: Model-based FPC with 2D linear-combination modeling is feasible and has great potential to improve metabolite level estimation for conventional and dynamic MRS data, especially for low-SNR conditions, e.g., long TEs or strong diffusion weighting.

Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation.

PURPOSE: The interest in applying and modeling dynamic MRS has recently grown. Two-dimensional modeling yields advantages for the precision of metabolite estimation in interrelated MRS data. However, it is unknown whether including all transients simultaneously in a 2D model without averaging (presuming a stable signal) performs similarly to one-dimensional (1D) modeling of the averaged spectrum. Therefore, we systematically investigated the accuracy, precision, and uncertainty estimation of both described model approaches. METHODS: Monte Carlo simulations of synthetic MRS data were used to compare the accuracy and uncertainty estimation of simultaneous 2D multitransient linear-combination modeling (LCM) with 1D-LCM of the average. A total of 2,500 data sets per condition with different noise representations of a 64-transient MRS experiment at six signal-to-noise levels for two separate spin systems (scyllo-inositol and gamma-aminobutyric acid) were analyzed. Additional data sets with different levels of noise correlation were also analyzed. Modeling accuracy was assessed by determining the relative bias of the estimated amplitudes against the ground truth, and modeling precision was determined by SDs and Cramér-Rao lower bounds (CRLBs). RESULTS: Amplitude estimates for 1D- and 2D-LCM agreed well and showed a similar level of bias compared with the ground truth. Estimated CRLBs agreed well between both models and with ground-truth CRLBs. For correlated noise, the estimated CRLBs increased with the correlation strength for the 1D-LCM but remained stable for the 2D-LCM. CONCLUSION: Our results indicate that the model performance of 2D multitransient LCM is similar to averaged 1D-LCM. This validation on a simplified scenario serves as a necessary basis for further applications of 2D modeling.

PR55α-controlled protein phosphatase 2A inhibits p16 expression and blocks cellular senescence induction by γ-irradiation.

Cellular senescence is a permanent cell cycle arrest that can be triggered by both internal and external genotoxic stressors, such as telomere dysfunction and DNA damage. The execution of senescence is mainly by two pathways, p16/RB and p53/p21, which lead to CDK4/6 inhibition and RB activation to block cell cycle progression. While the regulation of p53/p21 signaling in response to DNA damage and other insults is well-defined, the regulation of the p16/RB pathway in response to various stressors remains poorly understood. Here, we report a novel function of PR55α, a regulatory subunit of PP2A Ser/Thr phosphatase, as a potent inhibitor of p16 expression and senescence induction by ionizing radiation (IR), such as γ-rays. The results show that ectopic PR55α expression in normal pancreatic cells inhibits p16 transcription, increases RB phosphorylation, and blocks IR-induced senescence. Conversely, PR55α-knockdown by shRNA in pancreatic cancer cells elevates p16 transcription, reduces RB phosphorylation, and triggers senescence induction after IR. Furthermore, this PR55α function in the regulation of p16 and senescence is p53-independent because it was unaffected by the mutational status of p53. Moreover, PR55α only affects p16 expression but not p14 (ARF) expression, which is also transcribed from the same CDKN2A locus but from an alternative promoter. In normal human tissues, levels of p16 and PR55α proteins were inversely correlated and mutually exclusive. Collectively, these results describe a novel function of PR55α/PP2A in blocking p16/RB signaling and IR-induced cellular senescence.

Brain glutathione and GABA+ levels in autistic children.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a cohort of children aged 8-12 years with ASD (n = 52) and typically developing children (TDC, n = 49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.

Simultaneous multi-transient linear-combination modeling of MRS data improves uncertainty estimation.

Purpose: The interest in applying and modeling dynamic MRS has recently grown. 2D modeling yields advantages for the precision of metabolite estimation in interrelated MRS data. However, it is unknown whether including all transients simultaneously in a 2D model without averaging (presuming a stable signal) performs similarly to 1D modeling of the averaged spectrum. Therefore, we systematically investigated the accuracy, precision, and uncertainty estimation of both described model approaches. Methods: Monte Carlo simulations of synthetic MRS data were used to compare the accuracy and uncertainty estimation of simultaneous 2D multi-transient LCM with 1D-LCM of the average. 2,500 datasets per condition with different noise representations of a 64-transient MRS experiment at 6 signal-to-noise levels for two separate spin systems (scyllo-inositol and GABA) were analyzed. Additional datasets with different levels of noise correlation were also analyzed. Modeling accuracy was assessed by determining the relative bias of the estimated amplitudes against the ground truth, and modeling precision was determined by standard deviations and Cramér-Rao Lower Bounds (CRLB). Results: Amplitude estimates for 1D- and 2D-LCM agreed well and showed similar level of bias compared to the ground truth. Estimated CRLBs agreed well between both models and with ground truth CRLBs. For correlated noise the estimated CRLBs increased with the correlation strength for the 1D-LCM but remained stable for the 2D-LCM. Conclusion: Our results indicate that the model performance of 2D multi-transient LCM is similar to averaged 1D-LCM. This validation on a simplified scenario serves as necessary basis for further applications of 2D modeling.

Initial experience with an electron FLASH research extension (FLEX) for the Clinac system.

PURPOSE: Radiotherapy delivered at ultra-high-dose-rates (≥40 Gy/s), that is, FLASH, has the potential to effectively widen the therapeutic window and considerably improve the care of cancer patients. The underlying mechanism of the FLASH effect is not well understood, and commercial systems capable of delivering such dose rates are scarce. The purpose of this study was to perform the initial acceptance and commissioning tests of an electron FLASH research product for preclinical studies. METHODS: A linear accelerator (Clinac 23EX) was modified to include a non-clinical FLASH research extension (the Clinac-FLEX system) by Varian, a Siemens Healthineers company (Palo Alto, CA) capable of delivering a 16 MeV electron beam with FLASH and conventional dose rates. The acceptance, commissioning, and dosimetric characterization of the FLEX system was performed using radiochromic film, optically stimulated luminescent dosimeters, and a plane-parallel ionization chamber. A radiation survey was conducted for which the shielding of the pre-existing vault was deemed sufficient. RESULTS: The Clinac-FLEX system is capable of delivering a 16 MeV electron FLASH beam of approximately 1 Gy/pulse at isocenter and reached a maximum dose rate >3.8 Gy/pulse near the upper accessory mount on the linac gantry. The percent depth dose curves of the 16 MeV FLASH and conventional modes for the 10 × 10 cm2 applicator agreed within 0.5 mm at a range of 50% of the maximum dose. Their respective profiles agreed well in terms of flatness but deviated for field sizes >10 × 10 cm2 . The output stability of the FLASH system exhibited a dose deviation of <1%. Preliminary cell studies showed that the FLASH dose rate (180 Gy/s) had much less impact on the cell morphology of 76N breast normal cells compared to the non-FLASH dose rate (18 Gy/s), which induced large-size cells. CONCLUSION: Our studies characterized the non-clinical Clinac-FLEX system as a viable solution to conduct FLASH research that could substantially increase access to ultra-high-dose-rate capabilities for scientists.

sLASER and PRESS perform similarly at revealing metabolite-age correlations at 3 T.

PURPOSE: To compare the respective ability of PRESS and sLASER to reveal biological relationships, using age as a validation covariate at 3 T. METHODS: MRS data were acquired from 102 healthy volunteers using PRESS and sLASER in centrum semiovale and posterior cingulate cortex (PCC). Acquisition parameters included TR/TE = 2000/30 ms, 96 transients, and 2048 datapoints sampled at 2 kHz. Spectra were analyzed using Osprey. SNR, FWHM linewidth of total creatine, and metabolite concentrations were extracted. A linear model was used to compare SNR and linewidth. Paired t-tests were used to assess differences in metabolite measurements between PRESS and sLASER. Correlations were used to evaluate the relationship between PRESS and sLASER metabolite estimates, as well as the strength of each metabolite-age relationship. Coefficients of variation were calculated to assess inter-subject variability in each metabolite measurement. RESULTS: SNR and linewidth were significantly higher (p < 0.01) for sLASER than PRESS in PCC. Paired t-tests showed significant differences between PRESS and sLASER in most metabolite measurements. PRESS-sLASER measurements were significantly correlated (p < 0.05) for most metabolites. Metabolite-age relationships were consistently identified using both methods. Similar coefficients of variation were observed for most metabolites. CONCLUSION: The study results suggest strong agreement between PRESS and sLASER in identifying relationships between brain metabolites and age in centrum semiovale and PCC data acquired at 3 T. sLASER is technically desirable due to the reduced chemical shift displacement artifact; however, PRESS performed similarly in homogeneous brain regions at clinical field strength.

Tackling the escalating burden of care in Uganda: a qualitative exploration of the challenges experienced by family carers of patients with chronic non-communicable diseases.

BACKGROUND: Family carers face challenges that could significantly affect their health and the health of those they care for. However, these challenges are not well documented in low-income settings, including Uganda. We explored the challenges of caring for someone with chronic non-communicable disease (NCD) in Uganda. METHODS: We conducted a qualitative exploratory study at Hospice Africa, Uganda (an urban setting) and Hampton Health Center (a rural setting) in Uganda in February and March 2021. Family carers (n = 44) were recruited using snowball and purposive sampling techniques. Data were collected using focus group discussions and in-depth interviews, gathering family carer perspectives of (a) their caring role (b) their support needs, and (c) attitudes of the wider community. In total, four focus group discussions and 10 individual interviews were completed. RESULTS: The average age of carers was 46 years old. The majority of family care was provided by female relatives, who also experienced intersectional disadvantages relating to economic opportunities and employment. Family carers carried a huge burden of care, experiencing significant challenges that affected their physical health, and material and emotional well-being. These challenges also affected the quality of care of the patients for whom they cared. Carers struggled to provide for the basic needs of the patient including the provision of medication and transport to health facilities. Carers received no formal training and limited support to carry out the caring role. They reported that they had little understanding of the patient's illness, or how best to provide care. CONCLUSIONS: As NCDs continue to rise globally, the role of family caregivers is becoming more prominent. The need to support carers is an urgent concern. Family carer needs should be prioritised in policy and resource allocation. The need for a carer's toolkit of resources, and the enhancement of community support, have been identified.

Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients.

Introduction: Diffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessitate higher b-values to accurately characterize their diffusion properties. Ultra-strong gradients allow access to higher b-values per-unit time, higher SNR for a given b-value, and shorter diffusion times, but introduce additional challenges such as eddy-current artefacts, gradient non-uniformity, and mechanical vibrations. Methods: In this work, we present initial DW-MRS data acquired on a 3T Siemens Connectom scanner equipped with ultra-strong (300 mT/m) gradients. We explore the practical issues associated with this manner of acquisition, the steps that may be taken to mitigate their impact on the data, and the potential benefits of ultra-strong gradients for DW-MRS. An in-house DW-PRESS sequence and data processing pipeline were developed to mitigate the impact of these confounds. The interaction of TE, b-value, and maximum gradient amplitude was investigated using simulations and pilot data, whereby maximum gradient amplitude was restricted. Furthermore, two DW-MRS voxels in grey and white matter were acquired using ultra-strong gradients and high b-values. Results: Simulations suggest T2-based SNR gains that are experimentally confirmed. Ultra-strong gradient acquisitions exhibit similar artefact profiles to those of lower gradient amplitude, suggesting adequate performance of artefact mitigation strategies. Gradient field non-uniformity influenced ADC estimates by up to 4% when left uncorrected. ADC and Kurtosis estimates for tNAA, tCho, and tCr align with previously published literature. Discussion: In conclusion, we successfully implemented acquisition and data processing strategies for ultra-strong gradient DW-MRS and results indicate that confounding effects of the strong gradient system can be ameliorated, while achieving shorter diffusion times and improved metabolite SNR.

Brain Glutathione and GABA+ levels in autistic children.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a large cohort of children aged 8-12 years with ASD (n=52) and typically developing children (TDC, n=49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder.

The Arabinose 5-Phosphate Isomerase KdsD Is Required for Virulence in Burkholderia pseudomallei.

Burkholderia pseudomallei is the causative agent of melioidosis, which is endemic primarily in Southeast Asia and northern Australia but is increasingly being seen in other tropical and subtropical regions of the world. Melioidosis is associated with high morbidity and mortality rates, which is mediated by the wide range of virulence factors encoded by B. pseudomallei. These virulence determinants include surface polysaccharides such as lipopolysaccharide (LPS) and capsular polysaccharides (CPS). Here, we investigated a predicted arabinose-5-phosphate isomerase (API) similar to KdsD in B. pseudomallei strain K96243. KdsD is required for the production of the highly conserved 3-deoxy-d-manno-octulosonic acid (Kdo), a key sugar in the core region of LPS. Recombinant KdsD was expressed and purified, and API activity was determined. Although a putative API paralogue (KpsF) is also predicted to be encoded, the deletion of kdsD resulted in growth defects, loss of motility, reduced survival in RAW 264.7 murine macrophages, and attenuation in a BALB/c mouse model of melioidosis. Suppressor mutations were observed during a phenotypic screen for motility, revealing single nucleotide polymorphisms or indels located in the poorly understood CPS type IV cluster. Crucially, suppressor mutations did not result in reversion of attenuation in vivo. This study demonstrates the importance of KdsD for B. pseudomallei virulence and highlights further the complex nature of the polysaccharides it produces. IMPORTANCE The intrinsic resistance of B. pseudomallei to many antibiotics complicates treatment. This opportunistic pathogen possesses a wide range of virulence factors, resulting in severe and potentially fatal disease. Virulence factors as targets for drug development offer an alternative approach to combat pathogenic bacteria. Prior to initiating early drug discovery approaches, it is important to demonstrate that disruption of the target gene will prevent the development of disease. This study highlights the fact that KdsD is crucial for virulence of B. pseudomallei in an animal model of infection and provides supportive phenotypic characterization that builds a foundation for future therapeutic development.

Continuous Automated Analysis Workflow for MRS Studies.

Magnetic resonance spectroscopy (MRS) can non-invasively measure levels of endogenous metabolites in living tissue and is of great interest to neuroscience and clinical research. To this day, MRS data analysis workflows differ substantially between groups, frequently requiring many manual steps to be performed on individual datasets, e.g., data renaming/sorting, manual execution of analysis scripts, and manual assessment of success/failure. Manual analysis practices are a substantial barrier to wider uptake of MRS. They also increase the likelihood of human error and prevent deployment of MRS at large scale. Here, we demonstrate an end-to-end workflow for fully automated data uptake, processing, and quality review.The proposed continuous automated MRS analysis workflow integrates several recent innovations in MRS data and file storage conventions. They are efficiently deployed by a directory monitoring service that automatically triggers the following steps upon arrival of a new raw MRS dataset in a project folder: (1) conversion from proprietary manufacturer file formats into the universal format NIfTI-MRS; (2) consistent file system organization according to the data accumulation logic standard BIDS-MRS; (3) executing a command-line executable of our open-source end-to-end analysis software Osprey; (4) e-mail delivery of a quality control summary report for all analysis steps.The automated architecture successfully completed for a demonstration dataset. The only manual step required was to copy a raw data folder into a monitored directory.Continuous automated analysis of MRS data can reduce the burden of manual data analysis and quality control, particularly for non-expert users and multi-center or large-scale studies and offers considerable economic advantages.

Macrophage infectivity potentiator protein, a peptidyl prolyl cis-trans isomerase, essential for Coxiella burnetii growth and pathogenesis.

Coxiella burnetii is a Gram-negative intracellular pathogen that causes the debilitating disease Q fever, which affects both animals and humans. The only available human vaccine, Q-Vax, is effective but has a high risk of severe adverse reactions, limiting its use as a countermeasure to contain outbreaks. Therefore, it is essential to identify new drug targets to treat this infection. Macrophage infectivity potentiator (Mip) proteins catalyse the folding of proline-containing proteins through their peptidyl prolyl cis-trans isomerase (PPIase) activity and have been shown to play an important role in the virulence of several pathogenic bacteria. To date the role of the Mip protein in C. burnetii pathogenesis has not been investigated. This study demonstrates that CbMip is likely to be an essential protein in C. burnetii. The pipecolic acid derived compounds, SF235 and AN296, which have shown utility in targeting other Mip proteins from pathogenic bacteria, demonstrate inhibitory activities against CbMip. These compounds were found to significantly inhibit intracellular replication of C. burnetii in both HeLa and THP-1 cells. Furthermore, SF235 and AN296 were also found to exhibit antibiotic properties against both the virulent (Phase I) and avirulent (Phase II) forms of C. burnetii Nine Mile Strain in axenic culture. Comparative proteomics, in the presence of AN296, revealed alterations in stress responses with H2O2 sensitivity assays validating that Mip inhibition increases the sensitivity of C. burnetii to oxidative stress. In addition, SF235 and AN296 were effective in vivo and significantly improved the survival of Galleria mellonella infected with C. burnetii. These results suggest that unlike in other bacteria, Mip in C. burnetii is required for replication and that the development of more potent inhibitors against CbMip is warranted and offer potential as novel therapeutics against this pathogen.

Genetic deletion of skeletal muscle iPLA2γ results in mitochondrial dysfunction, muscle atrophy and alterations in whole-body energy metabolism.

Skeletal muscle is the major site of glucose utilization in mammals integrating serum glucose clearance with mitochondrial respiration. To mechanistically elucidate the roles of iPLA2γ in skeletal muscle mitochondria, we generated a skeletal muscle-specific calcium-independent phospholipase A2γ knockout (SKMiPLA2γKO) mouse. Genetic ablation of skeletal muscle iPLA2γ resulted in pronounced muscle weakness, muscle atrophy, and increased blood lactate resulting from defects in mitochondrial function impairing metabolic processing of pyruvate and resultant bioenergetic inefficiency. Mitochondria from SKMiPLA2γKO mice were dysmorphic displaying marked changes in size, shape, and interfibrillar juxtaposition. Mitochondrial respirometry demonstrated a marked impairment in respiratory efficiency with decreases in the mass and function of oxidative phosphorylation complexes and cytochrome c. Further, a pronounced decrease in mitochondrial membrane potential and remodeling of cardiolipin molecular species were prominent. Collectively, these alterations prevented body weight gain during high-fat feeding through enhanced glucose disposal without efficient capture of chemical energy thereby altering whole-body bioenergetics.