bbSelect - An Open-Source Tool for Performing a 3D Pharmacophore-Driven Diverse Selection of R-Groups.

The design of compounds during hit-to-lead often seeks to explore a vector from a core scaffold to form additional interactions with the target protein. A rational approach to this is to probe the region of a protein accessed by a vector with a systematic placement of pharmacophore features in 3D, particularly when bound structures are not available. Herein, we present bbSelect, an open-source tool built to map the placements of pharmacophore features in 3D Euclidean space from a library of R-groups, employing partitioning to drive a diverse and systematic selection to a user-defined size. An evaluation of bbSelect against established methods exemplified the superiority of bbSelect in its ability to perform diverse selections, achieving high levels of pharmacophore feature placement coverage with selection sizes of a fraction of the total set and without the introduction of excess complexity. bbSelect also reports visualizations and rationale to enable users to understand and interrogate results. This provides a tool for the drug discovery community to guide their hit-to-lead activities.

A spectroscopic liquid biopsy for the earlier detection of multiple cancer types.

BACKGROUND: A rapid, low-cost blood test that can be applied to reliably detect multiple different cancer types would be transformational. METHODS: In this large-scale discovery study (n = 2092 patients) we applied the Dxcover® Cancer Liquid Biopsy to examine eight different cancers. The test uses Fourier transform infrared (FTIR) spectroscopy and machine-learning algorithms to detect cancer. RESULTS: Area under the receiver operating characteristic curve (ROC) values were calculated for eight cancer types versus symptomatic non-cancer controls: brain (0.90), breast (0.76), colorectal (0.91), kidney (0.91), lung (0.91), ovarian (0.86), pancreatic (0.84) and prostate (0.86). We assessed the test performance when all eight cancer types were pooled to classify 'any cancer' against non-cancer patients. The cancer versus asymptomatic non-cancer classification detected 64% of Stage I cancers when specificity was 99% (overall sensitivity 57%). When tuned for higher sensitivity, this model identified 99% of Stage I cancers (with specificity 59%). CONCLUSIONS: This spectroscopic blood test can effectively detect early-stage disease and can be fine-tuned to maximise either sensitivity or specificity depending on the requirements from different healthcare systems and cancer diagnostic pathways. This low-cost strategy could facilitate the requisite earlier diagnosis, when cancer treatment can be more effective, or less toxic. STATEMENT OF TRANSLATIONAL RELEVANCE: The earlier diagnosis of cancer is of paramount importance to improve patient survival. Current liquid biopsies are mainly focused on single tumour-derived biomarkers, which limits test sensitivity, especially for early-stage cancers that do not shed enough genetic material. This pan-omic liquid biopsy analyses the full complement of tumour and immune-derived markers present within blood derivatives and could facilitate the earlier detection of multiple cancer types. There is a low barrier to integrating this blood test into existing diagnostic pathways since the technology is rapid, simple to use, only minute sample volumes are required, and sample preparation is minimal. In addition, the spectroscopic liquid biopsy described in this study has the potential to be combined with other orthogonal tests, such as cell-free DNA, which could provide an efficient route to diagnosis. Cancer treatment can be more effective when given earlier, and this low-cost strategy has the potential to improve patient prognosis.

Liquid biopsies: the future of cancer early detection.

Cancer is a worldwide pandemic. The burden it imposes grows steadily on a global scale causing emotional, physical, and financial strains on individuals, families, and health care systems. Despite being the second leading cause of death worldwide, many cancers do not have screening programs and many people with a high risk of developing cancer fail to follow the advised medical screening regime due to the nature of the available screening tests and other challenges with compliance. Moreover, many liquid biopsy strategies being developed for early detection of cancer lack the sensitivity required to detect early-stage cancers. Early detection is key for improved quality of life, survival, and to reduce the financial burden of cancer treatments which are greater at later stage detection. This review examines the current liquid biopsy market, focusing in particular on the strengths and drawbacks of techniques in achieving early cancer detection. We explore the clinical utility of liquid biopsy technologies for the earlier detection of solid cancers, with a focus on how a combination of various spectroscopic and -omic methodologies may pave the way for more efficient cancer diagnostics.

Intraparenchymal convection enhanced delivery of AAV in sheep to treat Mucopolysaccharidosis IIIC.

BACKGROUND: Mucopolysaccharidosis IIIC (MPSIIIC) is one of four Sanfilippo diseases sharing clinical symptoms of severe cognitive decline and shortened lifespan. The missing enzyme, heparan sulfate acetyl-CoA: α-glucosaminide-N-acetyltransferase (HGSNAT), is bound to the lysosomal membrane, therefore cannot cross the blood-brain barrier or diffuse between cells. We previously demonstrated disease correction in MPSIIIC mice using an Adeno-Associated Vector (AAV) delivering HGSNAT via intraparenchymal brain injections using an AAV2 derived AAV-truetype (AAV-TT) serotype with improved distribution over AAV9. METHODS: Here, intraparenchymal AAV was delivered in sheep using catheters or Hamilton syringes, placed using Brainlab cranial navigation for convection enhanced delivery, to reduce proximal vector expression and improve spread. RESULTS: Hamilton syringes gave improved AAV-GFP distribution, despite lower vector doses and titres. AAV-TT-GFP displayed moderately better transduction compared to AAV9-GFP but both serotypes almost exclusively transduced neurons. Functional HGSNAT enzyme was detected in 24-37% of a 140g gyrencephalic sheep brain using AAV9-HGSNAT with three injections in one hemisphere. CONCLUSIONS: Despite variabilities in volume and titre, catheter design may be critical for efficient brain delivery. These data help inform a clinical trial for MPSIIIC.

Augmentation of FTIR spectral datasets using Wasserstein generative adversarial networks for cancer liquid biopsies.

Over recent years, deep learning (DL) has become more widely used within the field of cancer diagnostics. However, DL often requires large training datasets to prevent overfitting, which can be difficult and expensive to acquire. Data augmentation is a method that can be used to generate new data points to train DL models. In this study, we use attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectra of patient dried serum samples and compare non-generative data augmentation methods to Wasserstein generative adversarial networks (WGANs) in their ability to improve the performance of a convolutional neural network (CNN) to differentiate between pancreatic cancer and non-cancer samples in a total cohort of 625 patients. The results show that WGAN augmented spectra improve CNN performance more than non-generative augmented spectra. When compared with a model that utilised no augmented spectra, adding WGAN augmented spectra to a CNN with the same architecture and same parameters, increased the area under the receiver operating characteristic curve (AUC) from 0.661 to 0.757, presenting a 15% increase in diagnostic performance. In a separate test on a colorectal cancer dataset, data augmentation using a WGAN led to an increase in AUC from 0.905 to 0.955. This demonstrates the impact data augmentation can have on DL performance for cancer diagnosis when the amount of real data available for model training is limited.

Recurrent neural networks for time domain modelling of FTIR spectra: application to brain tumour detection.

Attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy alongside machine learning (ML) techniques is an emerging approach for the early detection of brain cancer in clinical practice. A crucial step in the acquisition of an IR spectrum is the transformation of the time domain signal from the biological sample to a frequency domain spectrum via a discrete Fourier transform. Further pre-processing of the spectrum is typically applied to reduce non-biological sample variance, and thus to improve subsequent analysis. However, the Fourier transformation is often assumed to be essential even though modelling of time domain data is common in other fields. We apply an inverse Fourier transform to frequency domain data to map these to the time domain. We use the transformed data to develop deep learning models utilising Recurrent Neural Networks (RNNs) to differentiate between brain cancer and control in a cohort of 1438 patients. The best performing model achieves a mean (cross-validated score) area under the receiver operating characteristic (ROC) curve (AUC) of 0.97 with sensitivity of 0.91 and specificity of 0.91. This is better than the optimal model trained on frequency domain data which achieves an AUC of 0.93 with sensitivity of 0.85 and specificity of 0.85. A dataset comprising 385 patient samples which were prospectively collected in the clinic is used to test a model defined with the best performing configuration and fit to the time domain. Its classification accuracy is found to be comparable to the gold-standard for this dataset demonstrating that RNNs can accurately classify disease states using spectroscopic data represented in the time domain.

Blinded Predictions and Post Hoc Analysis of the Second Solubility Challenge Data: Exploring Training Data and Feature Set Selection for Machine and Deep Learning Models.

Accurate methods to predict solubility from molecular structure are highly sought after in the chemical sciences. To assess the state of the art, the American Chemical Society organized a "Second Solubility Challenge" in 2019, in which competitors were invited to submit blinded predictions of the solubilities of 132 drug-like molecules. In the first part of this article, we describe the development of two models that were submitted to the Blind Challenge in 2019 but which have not previously been reported. These models were based on computationally inexpensive molecular descriptors and traditional machine learning algorithms and were trained on a relatively small data set of 300 molecules. In the second part of the article, to test the hypothesis that predictions would improve with more advanced algorithms and higher volumes of training data, we compare these original predictions with those made after the deadline using deep learning models trained on larger solubility data sets consisting of 2999 and 5697 molecules. The results show that there are several algorithms that are able to obtain near state-of-the-art performance on the solubility challenge data sets, with the best model, a graph convolutional neural network, resulting in an RMSE of 0.86 log units. Critical analysis of the models reveals systematic differences between the performance of models using certain feature sets and training data sets. The results suggest that careful selection of high quality training data from relevant regions of chemical space is critical for prediction accuracy but that other methodological issues remain problematic for machine learning solubility models, such as the difficulty in modeling complex chemical spaces from sparse training data sets.

Solvation entropy, enthalpy and free energy prediction using a multi-task deep learning functional in 1D-RISM.

Simultaneous calculation of entropies, enthalpies and free energies has been a long-standing challenge in computational chemistry, partly because of the difficulty in obtaining estimates of all three properties from a single consistent simulation methodology. This has been particularly true for methods from the Integral Equation Theory of Molecular Liquids such as the Reference Interaction Site Model which have traditionally given large errors in solvation thermodynamics. Recently, we presented pyRISM-CNN, a combination of the 1 Dimensional Reference Interaction Site Model (1D-RISM) solver, pyRISM, with a deep learning based free energy functional, as a method of predicting solvation free energy (SFE). With this approach, a 40-fold improvement in prediction accuracy was delivered for a multi-solvent, multi-temperature dataset when compared to the standard 1D-RISM theory [Fowles et al., Digital Discovery, 2023, 2, 177-188]. Here, we report three further developments to the pyRISM-CNN methodology. Firstly, solvation free energies have been introduced for organic molecular ions in methanol or water solvent systems at 298 K, with errors below 4 kcal mol-1 obtained without the need for corrections or additional descriptors. Secondly, the number of solvents in the training data has been expanded from carbon tetrachloride, water and chloroform to now also include methanol. For neutral solutes, prediction errors nearing or below 1 kcal mol-1 are obtained for each organic solvent system at 298 K and water solvent systems at 273-373 K. Lastly, pyRISM-CNN was successfully applied to the simultaneous prediction of solvation enthalpy, entropy and free energy through a multi-task learning approach, with errors of 1.04, 0.98 and 0.47 kcal mol-1, respectively, for water solvent systems at 298 K.

A Type 1 Aldolase, NahE, Catalyzes a Stereoselective Nitro-Michael Reaction: Synthesis of ß-Aryl-γ-nitrobutyric Acids.

Michael addition reactions are highly useful in organic synthesis and are commonly accomplished using organocatalysts. However, the corresponding biocatalytic Michael additions are rare, typically lack synthetically useful substrate scope, and suffer from low stereoselectivity. Herein we report a biocatalytic nitro-Michael addition, catalyzed by NahE, that proceeds with low catalyst loading at room temperature in moderate to excellent enantioselectivity and high yields. A series of ß-nitrostyrenes reacted with pyruvate in the presence of NahE to give, after oxidative decarboxylation, ß-aryl-γ-nitrobutyric acids in up to 99 % yield without need for chromatography, providing a simple preparative-scale route to chiral GABA analogues. This reaction represents the first example of an aldolase displaying promiscuous Michaelase activity and opens the use of nitroalkenes in place of aldehydes as substrates for aldolases.

Phosphonate and α-Fluorophosphonate Analogues of d-Glucose 6-Phosphate as Active-Site Probes of 1l-myo-Inositol 1-Phosphate Synthase.

The biosynthesis of myo-inositol (mI) is central to the function of many organisms across all kingdoms of life. The first and rate-limiting step in this pathway is catalyzed by 1l-myo-inositol 1-phosphate synthase (mIPS), which converts d-glucose 6-phosphate (G6P) into 1l-myo-inositol 1-phosphate (mI1P). Extensive studies have shown that this reaction occurs through a stepwise NAD+-dependent redox aldol cyclization mechanism producing enantiomerically pure mI1P. Although the stereochemical nature of the mechanism has been elucidated, there is a lack of understanding of the importance of amino acid residues in the active site. Crystal structures of mIPS in the ternary complex with substrate analogues and NAD(H) show different ligand orientations. We therefore proposed to use isosteric and isoelectronic analogues of G6P to probe the active site. Here, we report the synthesis of the methylenephosphonate, difluoromethylenephosphonate, and (R)- and (S)-monofluoromethylenephosphonate analogues of G6P and their evaluation as inhibitors of mIPS activity. While the CH2 and CF2 analogues were produced with slight modification of a previously described route, the CHF analogues were synthesized through a new, shorter pathway. Kinetic behavior shows that all compounds are reversible competitive inhibitors with respect to G6P, with Ki values in the order CF2 (0.18 mM) < (S)-CHF (0.24 mM) < (R)-CHF (0.59 mM) < CH2 (1.2 mM). Docking studies of these phosphonates using published crystal structures show that substitution of the oxygen atom of the substrate changes the conformation of the resulting inhibitors, altering the position of carbon-6 and carbon-5, and this change is more pronounced with fluorine substitution.

Phosphoenolpyruvate Mutase-Catalyzed C-P Bond Formation: Mechanistic Ambiguities and Opportunities.

Phosphonates are produced across all domains of life and used widely in medicine and agriculture. Biosynthesis almost universally originates from the enzyme phosphoenolpyruvate mutase (Ppm), EC 5.4.2.9, which catalyzes O-P bond cleavage in phosphoenolpyruvate (PEP) and forms a high energy C-P bond in phosphonopyruvate (PnPy). Mechanistic scrutiny of this unusual intramolecular O-to-C phosphoryl transfer began with the discovery of Ppm in 1988 and concluded in 2008 with computational evidence supporting a concerted phosphoryl transfer via a dissociative metaphosphate-like transition state. This mechanism deviates from the standard 'in-line attack' paradigm for enzymatic phosphoryl transfer that typically involves a phosphoryl-enzyme intermediate, but definitive evidence is sparse. Here we review the experimental evidence leading to our current mechanistic understanding and highlight the roles of previously underappreciated conserved active site residues. We then identify remaining opportunities to evaluate overlooked residues and unexamined substrates/inhibitors.

Screening for phenotypic outliers identifies an unusually low concentration of a ß-lactoglobulin B protein isoform in bovine milk caused by a synonymous SNP.

BACKGROUND: Milk samples from 10,641 dairy cattle were screened by a mass spectrometry method for extreme concentrations of the A or B isoforms of the whey protein, ß-lactoglobulin (BLG), to identify causative genetic variation driving changes in BLG concentration. RESULTS: A cohort of cows, from a single sire family, was identified that produced milk containing a low concentration of the BLG B protein isoform. A genome-wide association study (GWAS) of BLG B protein isoform concentration in milk from AB heterozygous cows, detected a group of highly significant single nucleotide polymorphisms (SNPs) within or close to the BLG gene. Among these was a synonymous G/A variation at position + 78 bp in exon 1 of the BLG gene (chr11:103256256G > A). The effect of the A allele of this SNP (which we named B') on BLG expression was evaluated in a luciferase reporter assay in transfected CHO-K1 and MCF-7 cells. In both cell types, the presence of the B' allele in a plasmid containing the bovine BLG gene from -922 to + 898 bp (relative to the transcription initiation site) resulted in a 60% relative reduction in mRNA expression, compared to the plasmid containing the wild-type B sequence allele. Examination of a mammary RNAseq dataset (n = 391) identified 14 heterozygous carriers of the B' allele which were homozygous for the BLG B protein isoform (BB'). The level of expression of the BLG B' allele was 41.9 ± 1.0% of that of the wild-type BLG B allele. Milk samples from three cows, homozygous for the A allele at chr11:103,256,256 (B'B'), were analysed (HPLC) and showed BLG concentrations of 1.04, 1.26 and 1.83 g/L relative to a mean of 4.84 g/L in milk from 16 herd contemporaries of mixed (A and B) BLG genotypes. The mechanism by which B' downregulates milk BLG concentration remains to be determined. CONCLUSIONS: High-throughput screening and identification of outliers, enabled the discovery of a synonymous G > A mutation in exon 1 of the B allele of the BLG gene (B'), which reduced the milk concentration of ß-lactoglobulin B protein isoform, by more than 50%. Milk from cows carrying the B' allele is expected to have improved processing characteristics, particularly for cheese-making.

Association Between Hyperoxemia and Increased Cell-Free Plasma Hemoglobin During Cardiopulmonary Bypass in Infants and Children.

OBJECTIVES: To determine potential risk factors for severe hemolysis during pediatric cardiopulmonary bypass and examine whether supraphysiologic levels of oxygen and cardiopulmonary bypass duration are associated with hemolysis. DESIGN: Prospective observational study. SETTING: Cardiac ICU in a university-affiliated children's hospital. PATIENTS: Greater than 1 month to less than 18 years old patients undergoing cardiopulmonary bypass for cardiac surgery. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Plasma samples from 100 patients to assess cell-free plasma hemoglobin levels were obtained at start cardiopulmonary bypass, at the end of cardiopulmonary bypass, and 2 and 24 hours after reperfusion. Arterial blood gas samples were obtained before and every 30 minutes during cardiopulmonary bypass. Patient demographics and laboratory data were collected from the electronic medical record. Plasma hemoglobin levels peaked at the end of cardiopulmonary bypass and haptoglobin levels continued to fall throughout all time points. There were 44 patients with severe hemolysis (change in cell-free plasma hemoglobin > 50 mg/dL). Younger age (odds ratio/sd 0.45 [95% CI, 0.25-0.81]) and higher mean Pao2 × cardiopulmonary bypass duration (31.11 [1.46-664.64]) were identified as risk factors for severe hemolysis in multivariable analysis. Severe hemolysis was associated with longer hospital and ICU lengths of stay as well as acute kidney injury. CONCLUSIONS: We observed younger age and the exposure to both oxygen and duration of cardiopulmonary bypass as risk factors for hemolysis. Oxygen delivery through the cardiopulmonary bypass circuit is an easily modifiable risk factor. Its role in the production of reactive oxygen species that could alter the erythrocyte membrane deserves further examination in larger prospective studies.

Incoherent range-based holography of far-distant objects using LIDAR.

Los Alamos National Laboratory has developed an incoherent, long-range, sub-centimeter resolution (LIDAR) with which we achieve centimeter-scale reflection holography at extremely long ranges. The system consists of a pulsed laser and photon-counting receiver. This combination yields round-trip time of flight data to illuminate parts of the object of interest. The aggregation of these data for many LIDAR pulses yields a plot with a range on the X axis and reflectance on the Y axis, which we refer to as a range profile. Observing that the range profile is a projection of the reflection map of the object onto the view vector, we collect profiles from a variety of viewing angles and invert these data to form an image. We adapt imaging algorithms from the field of computer aided tomography to suit our application and present results from imaging demonstrations at a 10 km range.

Unbound vitamin D concentrations are not decreased in critically ill patients.

BACKGROUND: Free concentrations of highly protein bound hormones, such as cortisol and thyroxine, are unchanged in critical illness despite substantial decreases in total concentration. Total 25-hydroxyvitamin D (25(OH)D) concentration is decreased in critical illness, but the free concentration of 25(OH)D has had less attention. AIM: To compare total and calculated free 25(OH)D concentrations in critically ill patients with healthy controls. METHODS: In this case-control study, 38 patients with critical illness were compared with 68 healthy controls; 25(OH)D was measured by liquid chromatography tandem mass spectrometry (LCMS/MS) and vitamin D binding protein (VDBP) by direct sandwich enzyme-linked immunosorbent assay. Total and calculated free 25(OH)D concentrations were compared using unpaired t-tests. RESULTS: Total 25(OH)D concentrations were significantly lower in critically ill patients than controls (37 (95% confidence interval 31-43) vs 57 (53-60) nmol/L). Calculated free concentrations of 25(OH)D were not lower in critically ill patients than healthy controls (26 (22-29) vs 19 (18-20) pmol/L). CONCLUSIONS: Calculated free 25(OH)D concentrations are not decreased in critical illness. Measuring total 25(OH)D concentrations in patients with critical illness potentially underestimates vitamin D and overestimates the number of patients who are deficient in vitamin D.

Characterization of an α-Glucosidase Enzyme Conserved in Gardnerella spp. Isolated from the Human Vaginal Microbiome.

Gardnerella spp. in the vaginal microbiome are associated with bacterial vaginosis, in which a lactobacillus-dominated community is replaced with mixed bacteria, including Gardnerella species. Co-occurrence of multiple Gardnerella species in the vaginal environment is common, but different species are dominant in different women. Competition for nutrients, including glycogen, could play an important role in determining the microbial community structure. Digestion of glycogen into products that can be taken up and further processed by bacteria requires the combined activities of several enzymes collectively known as amylases, which belong to glycoside hydrolase family 13 (GH13) within the CAZy classification system. GH13 is a large and diverse family of proteins, making prediction of their activities challenging. SACCHARIS annotation of the GH13 family in Gardnerella resulted in identification of protein domains belonging to eight subfamilies. Phylogenetic analysis of predicted amylase sequences from 26 genomes demonstrated that a putative α-glucosidase-encoding sequence, CG400_06090, was conserved in all Gardnerella spp. The predicted α-glucosidase enzyme was expressed, purified, and functionally characterized. The enzyme was active on a variety of maltooligosaccharides with maximum activity at pH 7. Km, kcat, and kcat/Km values for the substrate 4-nitrophenyl α-d-glucopyranoside were 8.3 µM, 0.96 min-1, and 0.11 µM-1 min-1, respectively. Glucose was released from maltose, maltotriose, maltotetraose, and maltopentaose, but no products were detected when the enzyme was incubated with glycogen. Our findings show that Gardnerella spp. produce an α-glucosidase enzyme that may contribute to the multistep process of glycogen metabolism by releasing glucose from maltooligosaccharides. IMPORTANCE Increased abundance of Gardnerella spp. is a diagnostic characteristic of bacterial vaginosis, an imbalance in the human vaginal microbiome associated with troubling symptoms, and negative reproductive health outcomes, including increased transmission of sexually transmitted infections and preterm birth. Competition for nutrients is likely an important factor in causing dramatic shifts in the vaginal microbial community but little is known about the contribution of bacterial enzymes to the metabolism of glycogen, a major carbon source available to vaginal bacteria. The significance of our research is characterizing the activity of an enzyme conserved in Gardnerella species that likely contributes to the ability of these bacteria to utilize glycogen.

Substrate Substitution in Kanosamine Biosynthesis Using Phosphonates and Phosphite Rescue.

Kanosamine is an antibiotic and antifungal compound synthesized from glucose 6-phosphate (G6P) in Bacillus subtilis by the action of three enzymes: NtdC, which catalyzes NAD-dependent oxidation of the C3-hydroxyl; NtdA, a PLP-dependent aminotransferase; and NtdB, a phosphatase. We previously demonstrated that NtdC can also oxidize substrates such as glucose and xylose, though at much lower rates, suggesting that the phosphoryloxymethylene moiety of the substrate is critical for effective catalysis. To probe this, we synthesized two phosphonate analogues of G6P in which the bridging oxygen is replaced by methylene and difluoromethylene groups. These analogues are substrates for NtdC, with second-order rate constants an order of magnitude lower than those for G6P. NtdA converts the resulting 3-keto products to the corresponding kanosamine 6-phosphonate analogues. We compared the rates to the rate of NtdC oxidation of glucose and xylose and showed that the low reactivity of xylose could be rescued 4-fold by the presence of phosphite, mimicking G6P in two pieces. These results allow the evaluation of the individual energetic contributions to catalysis of the bridging oxygen, the bridging C6 methylene, the phosphodianion, and the entropic gain of one substrate versus two substrate pieces. Phosphite also rescued the reversible formation 3-amino-3-deoxy-d-xylose by NtdA, demonstrating that truncated and nonhydrolyzable analogues of kanosamine 6-phosphate can be generated enzymatically.

Snapshots along the catalytic path of KabA, a PLP-dependent aminotransferase required for kanosamine biosynthesis in Bacillus cereus UW85.

Kanosamine is an antibiotic and antifungal monosaccharide. The kanosamine biosynthetic pathway from glucose 6-phosphate in Bacillus cereus UW85 was recently reported, and the functions of each of the three enzymes in the pathway, KabA, KabB and KabC, were demonstrated. KabA, a member of a subclass of the VIß family of PLP-dependent aminotransferases, catalyzes the second step in the pathway, generating kanosamine 6-phosphate (K6P) using l-glutamate as the amino-donor. KabA catalysis was shown to be extremely efficient, with a second-order rate constant with respect to K6P transamination of over 107 M-1s-1. Here we report the high-resolution structure of KabA in both the PLP- and PMP-bound forms. In addition, co-crystallization with K6P allowed the structure of KabA in complex with the covalent PLP-K6P adduct to be solved. Co-crystallization or soaking with glutamate or 2-oxoglutarate did not result in crystals with either substrate/product. Reduction of the PLP-KabA complex with sodium cyanoborohydride gave an inactivated enzyme, and crystals of the reduced KabA were soaked with the l-glutamate analog glutarate to mimic the KabA-PLP-l-glutamate complex. Together these four structures give a complete picture of how the active site of KabA recognizes substrates for each half-reaction. The KabA structure is discussed in the context of homologous aminotransferases.

Intravitreal gene therapy protects against retinal dysfunction and degeneration in sheep with CLN5 Batten disease.

Neuronal ceroid lipofuscinoses (NCL; Batten disease) are a group of inherited neurodegenerative diseases primarily affecting children. A common feature across most NCLs is the progressive loss of vision. We performed intravitreal injections of self-complementary AAV9 vectors packaged with either ovine CLN5 or CLN6 into one eye of 3-month-old CLN5-/- or CLN6-/- animals, respectively. Electroretinography (ERG) was performed every month following treatment, and retinal histology was assessed post-mortem in the treated compared to untreated eye. In CLN5-/- animals, ERG amplitudes were normalised in the treated eye whilst the untreated eye declined in a similar manner to CLN5 affected controls. In CLN6-/- animals, ERG amplitudes in both eyes declined over time although the treated eye showed a slower decline. Post-mortem examination revealed significant attenuation of retinal atrophy and lysosomal storage body accumulation in the treated eye compared with the untreated eye in CLN5-/- animals. This proof-of-concept study provides the first observation of efficacious intravitreal gene therapy in a large animal model of NCL. In particular, the single administration of AAV9-mediated intravitreal gene therapy can successfully ameliorate retinal deficits in CLN5-/- sheep. Combining ocular gene therapy with brain-directed therapy presents a promising treatment strategy to be used in future sheep trials aiming to halt neurological and retinal disease in CLN5 Batten disease.

A patient-focused survey to assess the effects of the COVID-19 pandemic and social guidelines on people with muscular dystrophy.

INTRODUCTION/AIMS: In this study, we examined the social and health impacts of the coronavirus disease 2019 (COVID-19) pandemic and social guidelines on people with muscular dystrophies. METHODS: A prospective de-identified electronic survey was distributed to adults with self-reported facioscapulohumeral muscular dystrophy (FSHD), myotonic dystrophy (DM), and limb-girdle muscular dystrophy (LGMD) enrolled in national registries or with patient advocacy groups. The COVID-19 Impact Survey was developed by muscular dystrophy experts in association with patient collaborators and advocacy groups. The Perceived Stress Scale was used to measure perceived stress. RESULTS: Respondents (n = 774: 56% FSHD; 35% DM, and 9% LGMD) were mostly women and middle-aged (range 19-87 y). Rates of COVID-19 infections were low (<1%), compliance with local social distancing guidelines and policies high (98%). Major challenges reported during the pandemic included: obtaining treatment (40%), managing stress (37%), social distancing (36%), and obtaining essentials (34%). The majority reported a slight worsening in their disease state. Respondents reported moderate stress levels (stress score = 15.4; range = 0-35), with higher stress levels reported by women and those under age 30 y. Three-quarters of participants who participated in telemedicine visits were satisfied with the encounters; however, most reported a preference for in-person visits. DISCUSSION: People with muscular dystrophy reported moderate stress and challenges during the COVID-19 pandemic. Interventions such as exercise and stress-coping strategies, including strategies specific to women or individuals <30 y, may be important. Further investigation is needed into the role of telemedicine in the care of individuals with muscular dystrophy.