Impact of the COVID-19 Pandemic on the Severity and Early Postoperative Outcomes of Acute Appendicitis.

Background The coronavirus disease 2019 (COVID-19) pandemic caused changes in surgical practice. For acute appendicitis (AA), measures to control the pandemic might hinder patients from seeking medical care timely, resulting in increasing severity, postoperative complications, and mortality. This study aimed to investigate whether the COVID-19 pandemic had a negative impact on the severity and postoperative outcomes of patients with AA. Methodology We retrospectively reviewed medical records of AA patients treated operatively at Nhan Dan Gia Dinh Hospital hospital from June 1st to September 30th in three consecutive years: pre-pandemic (2019)/Group 1, minor waves (2020)/Group 2, and major wave (2021)/Group 3 (2021). Data were collected focusing on the duration of symptoms, severity of AA, time from admission to operation, postoperative complications, and mortality. Results There were 1,055 patients, including 452 patients in Group 1, 409 in Group 2, and 194 in Group 3. The overall number of patients decreased mainly in non-complicated AA. The percentages of hospital admission after 24 hours gradually increased (20.8%, 27.9%, and 43.8%, p < 0.05). The percentages of complicated AA in Group 2 and Group 3 were statistically higher than in Group 1 (39% and 55% vs. 31%, p < 0.05). Waiting time for operation increased to five hours during the major wave. Laparoscopic appendectomy was performed in 98-99% of AA patients during the pandemic, with an early postoperative complication rate of 5-9% and a mortality rate of 0.2-1%. Conclusions Although the percentages of hospital admission after 24 hours and complicated AA increased, laparoscopic appendectomy was still feasible and effective and should be maintained as the standard management for AA during the COVID-19 pandemic.

Surgical gestures as a method to quantify surgical performance and predict patient outcomes.

How well a surgery is performed impacts a patient's outcomes; however, objective quantification of performance remains an unsolved challenge. Deconstructing a procedure into discrete instrument-tissue "gestures" is a emerging way to understand surgery. To establish this paradigm in a procedure where performance is the most important factor for patient outcomes, we identify 34,323 individual gestures performed in 80 nerve-sparing robot-assisted radical prostatectomies from two international medical centers. Gestures are classified into nine distinct dissection gestures (e.g., hot cut) and four supporting gestures (e.g., retraction). Our primary outcome is to identify factors impacting a patient's 1-year erectile function (EF) recovery after radical prostatectomy. We find that less use of hot cut and more use of peel/push are statistically associated with better chance of 1-year EF recovery. Our results also show interactions between surgeon experience and gesture types-similar gesture selection resulted in different EF recovery rates dependent on surgeon experience. To further validate this framework, two teams independently constructe distinct machine learning models using gesture sequences vs. traditional clinical features to predict 1-year EF. In both models, gesture sequences are able to better predict 1-year EF (Team 1: AUC 0.77, 95% CI 0.73-0.81; Team 2: AUC 0.68, 95% CI 0.66-0.70) than traditional clinical features (Team 1: AUC 0.69, 95% CI 0.65-0.73; Team 2: AUC 0.65, 95% CI 0.62-0.68). Our results suggest that gestures provide a granular method to objectively indicate surgical performance and outcomes. Application of this methodology to other surgeries may lead to discoveries on methods to improve surgery.

A multi-scale time-series dataset with benchmark for machine learning in decarbonized energy grids.

The electric grid is a key enabling infrastructure for the ambitious transition towards carbon neutrality as we grapple with climate change. With deepening penetration of renewable resources, the reliable operation of the electric grid becomes increasingly challenging. In this paper, we present PSML, a first-of-its-kind open-access multi-scale time-series dataset, to aid in the development of data-driven machine learning (ML)-based approaches towards reliable operation of future electric grids. The dataset is synthesized from a joint transmission and distribution electric grid to capture the increasingly important interactions and uncertainties of the grid dynamics, containing power, voltage and current measurements over multiple spatio-temporal scales. Using PSML, we provide state-of-the-art ML benchmarks on three challenging use cases of critical importance to achieve: (i) early detection, accurate classification and localization of dynamic disturbances; (ii) robust hierarchical forecasting of load and renewable energy; and (iii) realistic synthetic generation of physical-law-constrained measurements. We envision that this dataset will provide use-inspired ML research in safety-critical systems, while simultaneously enabling ML researchers to contribute towards decarbonization of energy sectors.

Interpretability and fairness evaluation of deep learning models on MIMIC-IV dataset.

The recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications. However, due to the nature of such deep black-boxed models, concerns about interpretability, fairness, and biases in healthcare scenarios where human lives are at stake call for a careful and thorough examination of both datasets and models. In this work, we focus on MIMIC-IV (Medical Information Mart for Intensive Care, version IV), the largest publicly available healthcare dataset, and conduct comprehensive analyses of interpretability as well as dataset representation bias and prediction fairness of deep learning models for in-hospital mortality prediction. First, we analyze the interpretability of deep learning mortality prediction models and observe that (1) the best-performing interpretability method successfully identifies critical features for mortality prediction on various prediction models as well as recognizing new important features that domain knowledge does not consider; (2) prediction models rely on demographic features, raising concerns in fairness. Therefore, we then evaluate the fairness of models and do observe the unfairness: (1) there exists disparate treatment in prescribing mechanical ventilation among patient groups across ethnicity, gender and age; (2) models often rely on racial attributes unequally across subgroups to generate their predictions. We further draw concrete connections between interpretability methods and fairness metrics by showing how feature importance from interpretability methods can be beneficial in quantifying potential disparities in mortality predictors. Our analysis demonstrates that the prediction performance is not the only factor to consider when evaluating models for healthcare applications, since high prediction performance might be the result of unfair utilization of demographic features. Our findings suggest that future research in AI models for healthcare applications can benefit from utilizing the analysis workflow of interpretability and fairness as well as verifying if models achieve superior performance at the cost of introducing bias.

Survival Analysis Using Surgeon Skill Metrics and Patient Factors to Predict Urinary Continence Recovery After Robot-assisted Radical Prostatectomy.

BACKGROUND: It has been shown that metrics recorded for instrument kinematics during robotic surgery can predict urinary continence outcomes. OBJECTIVE: To evaluate the contributions of patient and treatment factors, surgeon efficiency metrics, and surgeon technical skill scores, especially for vesicourethral anastomosis (VUA), to models predicting urinary continence recovery following robot-assisted radical prostatectomy (RARP). DESIGN, SETTING, AND PARTICIPANTS: Automated performance metrics (APMs; instrument kinematics and system events) and patient data were collected for RARPs performed from July 2016 to December 2017. Robotic Anastomosis Competency Evaluation (RACE) scores during VUA were manually evaluated. Training datasets included: (1) patient factors; (2) summarized APMs (reported over RARP steps); (3) detailed APMs (reported over suturing phases of VUA); and (4) technical skills (RACE). Feature selection was used to compress the dimensionality of the inputs. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The study outcome was urinary continence recovery, defined as use of 0 or 1 safety pads per day. Two predictive models (Cox proportional hazards [CoxPH] and deep learning survival analysis [DeepSurv]) were used. RESULTS AND LIMITATIONS: Of 115 patients undergoing RARP, 89 (77.4%) recovered their urinary continence and the median recovery time was 166 d (interquartile range [IQR] 82-337). VUAs were performed by 23 surgeons. The median RACE score was 28/30 (IQR 27-29). Among the individual datasets, technical skills (RACE) produced the best models (C index: CoxPH 0.695, DeepSurv: 0.708). Among summary APMs, posterior/anterior VUA yielded superior model performance over other RARP steps (C index 0.543-0.592). Among detailed APMs, metrics for needle driving yielded top-performing models (C index 0.614-0.655) over other suturing phases. DeepSurv models consistently outperformed CoxPH; both approaches performed best when provided with all the datasets. Limitations include feature selection, which may have excluded relevant information but prevented overfitting. CONCLUSIONS: Technical skills and "needle driving" APMs during VUA were most contributory. The best-performing model used synergistic data from all datasets. PATIENT SUMMARY: One of the steps in robot-assisted surgical removal of the prostate involves joining the bladder to the urethra. Detailed information on surgeon performance for this step improved the accuracy of predicting recovery of urinary continence among men undergoing this operation for prostate cancer.

DL4Burn: Burn Surgical Candidacy Prediction using Multimodal Deep Learning.

Burn wounds are most commonly evaluated through visual inspection to determine surgical candidacy, taking into account burn depth and individualized patient factors. This process, though cost effective, is subjective and varies by provider experience. Deep learning models can assist in burn wound surgical candidacy with predictions based on the wound and patient characteristics. To this end, we present a multimodal deep learning approach and a complementary mobile application - DL4Burn - for predicting burn surgical candidacy, to emulate the multi-factored approach used by clinicians. Specifically, we propose a ResNet50-based multimodal model and validate it using retrospectively obtained patient burn images, demographic, and injury data.

Involvement of CREB-regulated transcription coactivators (CRTC) in transcriptional activation of steroidogenic acute regulatory protein (Star) by ACTH.

Studies in vivo have suggested the involvement of CREB-regulated transcription coactivator (CRTC)2 on ACTH-induced transcription of the key steroidogenic protein, Steroidogenic Acute Regulatory (StAR). The present study uses two ACTH-responsive adrenocortical cell lines, to examine the role of CRTC on Star transcription. Here we show that ACTH-induced Star primary transcript, or heteronuclear RNA (hnRNA), parallels rapid increases in nuclear levels of the 3 isoforms of CRTC; CRTC1, CRTC2 and CRTC3. Furthermore, ACTH promotes recruitment of CRTC2 and CRTC3 by the Star promoter and siRNA knockdown of either CRTC3 or CRTC2 attenuates the increases in ACTH-induced Star hnRNA. Using pharmacological inhibitors of PKA, MAP kinase and calcineurin, we show that the effects of ACTH on Star transcription and CRTC nuclear translocation depend predominantly on the PKA pathway. The data provides evidence that CRTC2 and CRTC3, contribute to activation of Star transcription by ACTH, and that PKA/CRTC-dependent pathways are part of the multifactorial mechanisms regulating Star transcription.

Rapid Glucocorticoid Feedback Inhibition of ACTH Secretion Involves Ligand-Dependent Membrane Association of Glucocorticoid Receptors.

The hypothesis that rapid glucocorticoid inhibition of pituitary ACTH secretion mediates a feedforward/feedback mechanism responsible for the hourly glucocorticoid pulsatility was tested in cultured pituitary cells. Perifusion with 30 pM CRH caused sustained the elevation of ACTH secretion. Superimposed corticosterone pulses inhibited CRH-stimulated ACTH release, depending on prior glucocorticoid clearance. When CRH perifusion started after 2 hours of glucocorticoid-free medium, corticosterone levels in the stress range (1 µM) caused a delayed (25 min) and prolonged inhibition of CRH-stimulated ACTH secretion, up to 60 minutes after corticosterone withdrawal. In contrast, after 6 hours of glucocorticoid-free medium, basal corticosterone levels inhibited CRH-stimulated ACTH within 5 minutes, after rapid recovery 5 minutes after corticosterone withdrawal. The latter effect was insensitive to actinomycin D but was prevented by the glucocorticoid receptor antagonist, RU486, suggesting nongenomic effects of the classical glucocorticoid receptor. In hypothalamic-derived 4B cells, 10 nM corticosterone increased immunoreactive glucocorticoid receptor content in membrane fractions, with association and clearance rates paralleling the effects on ACTH secretion from corticotrophs. Corticosterone did not affect CRH-stimulated calcium influx, but in AtT-20 cells, it had biphasic effects on CRH-stimulated Src phosphorylation, with early inhibition and late stimulation, suggesting a role for Src phosphorylation on the rapid glucocorticoid feedback. The data suggest that the nongenomic/membrane effects of classical GR mediate rapid and reversible glucocorticoid feedback inhibition at the pituitary corticotrophs downstream of calcium influx. The sensitivity and kinetics of these effects is consistent with the hypothesis that pituitary glucocorticoid feedback is part of the mechanism for adrenocortical ultradian pulse generation.

Bacillus anthracis cell wall peptidoglycan but not lethal or edema toxins produces changes consistent with disseminated intravascular coagulation in a rat model.

BACKGROUND: Disseminated intravascular coagulation (DIC) appears to be important in the pathogenesis of Bacillus anthracis infection, but its causes are unclear. Although lethal toxin (LT) and edema toxin (ET) could contribute, B. anthracis cell wall peptidoglycan (PGN), not the toxins, stimulates inflammatory responses associated with DIC. METHODS AND RESULTS: To better understand the pathogenesis of DIC during anthrax, we compared the effects of 24-hour infusions of PGN, LT, ET, or diluent (control) on coagulation measures 6, 24, or 48 hours after infusion initiation in 135 rats. No control recipient died. Lethality rates (approximately 30%) did not differ among PGN, LT, and ET recipients (P = .78). Thirty-three of 35 deaths (94%) occurred between 6 and 24 hours after the start of challenge. Among challenge components, PGN most consistently altered coagulation measures. Compared with control at 6 hours, PGN decreased platelet and fibrinogen levels and increased prothrombin and activated partial thromboplastin times and tissue factor, tissue factor pathway inhibitor, protein C, plasminogen activator inhibitor (PAI), and thrombin-antithrombin complex levels, whereas LT and ET only decreased the fibrinogen level or increased the PAI level (P ≤ .05). Nearly all effects associated with PGN infusion significantly differed from changes associated with toxin infusion (P ≤ .05 for all comparisons except for PAI level). CONCLUSION: DIC during B. anthracis infection may be related more to components such as PGN than to LT or ET.

Evidence for helical structure in a tetramer of α2-8 sialic acid: unveiling a structural antigen.

Characteristic H-bonding patterns define secondary structure in proteins and nucleic acids. We show that similar patterns apply for α2-8 sialic acid (SiA) in H(2)O and that H-bonds define its structure. A (15)N,(13)C α2-8 SiA tetramer, (SiA)(4), was used as a model system for the polymer. At 263 K, we detected intra-residue through-H-bond J couplings between (15)N and C8 for residues R-I-R-III of the tetramer, indicating H-bonds between the (15)N's and the O8's of these residues. Additional J couplings between the (15)N's and C2's of the adjacent residues confirm the putative H-bonds. NH groups showing this long-range correlation also experience slower (1)H/(2)H exchange. Additionally, detection of couplings between H7 and C2 for R-II and R-III implies that the conformations of the linkers between these residues are different than in the monomers. These structural elements are consistent with two left-handed helical models: 2 residues/turn (2(4) helix) and 4 residues/turn (1(4) helix). To discriminate between models, we resorted to (1)H,(1)H NOEs. The 2(4) helical model is in better agreement with the experimental data. We provide direct evidence of H-bonding for (SiA)(4) and show how H-bonds can be a determining factor for shaping its 3D structure.

The role of Cra in regulating acetate excretion and osmotic tolerance in E. coli K-12 and E. coli B at high density growth.

BACKGROUND: E. coli B (BL21), unlike E.coli K-12 (JM109) is insensitive to glucose concentration and, therefore, grows faster and produces less acetate than E. coli K-12, especially when growing to high cell densities at high glucose concentration. By performing genomic analysis, it was demonstrated that the cause of this difference in sensitivity to the glucose concentration is the result of the differences in the central carbon metabolism activity. We hypothesized that the global transcription regulator Cra (FruR) is constitutively expressed in E. coli B and may be responsible for the different behaviour of the two strains. To investigate this possibility and better understand the function of Cra in the two strains, cra - negative E. coli B (BL21) and E. coli K-12 (JM109) were prepared and their growth behaviour and gene expression at high glucose were evaluated using microarray and real-time PCR. RESULTS: The deletion of the cra gene in E. coli B (BL21) minimally affected the growth and maximal acetate accumulation, while the deletion of the same gene in E.coli K-12 (JM109) caused the cells to stop growing as soon as acetate concentration reached 6.6 g/L and the media conductivity reached 21 mS/cm. ppsA (gluconeogenesis gene), aceBA (the glyoxylate shunt genes) and poxB (the acetate producing gene) were down-regulated in both strains, while acs (acetate uptake gene) was down-regulated only in E.coli B (BL21). These transcriptional differences had little effect on acetate and pyruvate production. Additionally, it was found that the lower growth of E. coli K-12 (JM109) strain was the result of transcription inhibition of the osmoprotectant producing bet operon (betABT). CONCLUSIONS: The transcriptional changes caused by the deletion of cra gene did not affect the activity of the central carbon metabolism, suggesting that Cra does not act alone; rather it interacts with other pleiotropic regulators to create a network of metabolic effects. An unexpected outcome of this work is the finding that cra deletion caused transcription inhibition of the bet operon in E. coli K-12 (JM109) but did not affect this operon transcription in E. coli B (BL21). This property, together with the insensitivity to high glucose concentrations, makes this the E. coli B (BL21) strain more resistant to environmental changes.

Production, purification, and characterization of human alpha1 proteinase inhibitor from Aspergillus niger.

Human alpha one proteinase inhibitor (alpha1-PI) was cloned and expressed in Aspergillus niger, filamentious fungus that can grow in defined media and can perform glycosylation. Submerged culture conditions were established using starch as carbon source, 30% dissolved oxygen concentration, pH 7.0 and 28 degrees C. Eight milligrams per liter of active alpha1-PI were secreted to the growth media in about 40 h. Controlling the protein proteolysis was found to be an important factor in the production. The effects of various carbon sources, pH and temperature on the production and stability of the protein were tested and the product was purified and characterized. Two molecular weights variants of the recombinant alpha1-PI were produced by the fungus; the difference is attributed to the glycosylated part of the molecule. The two glycoproteins were treated with PNGAse F and the released glycans were analyzed by HPAEC, MALDI/TOF-MS, NSI-MS(n), and GC-MS. The MALDI and NSI- full MS spectra of permethylated N-glycans revealed that the N-glycans of both variants contain a series of high-mannose type glycans with 5-20 hexose units. Monosaccharide analysis showed that these were composed of N-acetylglucos-amine, mannose, and galactose. Linkage analysis revealed that the galactosyl component was in the furanoic conformation, which was attaching in a terminal non-reducing position. The Galactofuranose-containing high-mannnose type N-glycans are typical structures, which recently have been found as part of several glycoproteins produced by Aspergillus niger.

Modified Escherichia coli B (BL21), a superior producer of plasmid DNA compared with Escherichia coli K (DH5alpha).

Plasmid DNA (pDNA) is an emerging experimental vaccine, produced in E. coli, initially targeted for viral diseases. Unlike traditional protein vaccines whose average dose is micrograms, the average dose of pDNA is on the scale of milligrams. Production yields are, therefore, important for the future development of this vaccine. The E. coli strains currently used for pDNA production, JM109 and DH5alpha, are both suitable for production of stable pDNA due to the deletion of recA and endA, however, these two E. coli K strains are sensitive to growth conditions such as high glucose concentration. On the other hand E. coli BL21 is less sensitive to growth conditions than E. coli JM109 or DH5alpha, this strain grows to higher densities and due to its active glyoxylate shunt and anaplerotic pathways is not sensitive to high glucose concentration. This strain is used for recombinant protein production but not for pDNA production because of its inability to produce stable pDNA. To adapt E. coli BL21 for stable pDNA production, the strain was mutated by deleting both recA and endA, and a proper growth and production strategy was developed. Production values, reaching 2 g/L were obtained using glucose as a carbon source. The produced plasmid, which was constructed for HIV clinical study, was found to have identical properties to the plasmid currently produced by E. coli DH5alpha.

Expression of human alpha1-proteinase inhibitor in Aspergillus niger.

BACKGROUND: Human alpha1-proteinase inhibitor (alpha1-PI), also known as antitrypsin, is the most abundant serine protease inhibitor (serpin) in plasma. Its deficiency is associated with development of progressive, ultimately fatal emphysema. Currently in the United States, alpha1-PI is available for replacement therapy as an FDA licensed plasma-derived (pd) product. However, the plasma source itself is limited; moreover, even with efficient viral inactivation steps used in manufacture of plasma products, the risk of contamination from emerging viruses may still exist. Therefore, recombinant alpha1-PI (r-alpha1-PI) could provide an attractive alternative. Although r-alpha1-PI has been produced in several hosts, protein stability in vitro and rapid clearance from the circulation have been major issues, primarily due to absent or altered glycosylation. RESULTS: We have explored the possibility of expressing the gene for human alpha1-PI in the filamentous fungus Aspergillus niger (A. niger), a system reported to be capable of providing more "mammalian-like" glycosylation patterns to secretable proteins than commonly used yeast hosts. Our expression strategy was based on fusion of alpha1-PI with a strongly expressed, secreted leader protein (glucoamylase G2), separated by dibasic processing site (N-V-I-S-K-R) that provides in vivo cleavage. SDS-PAGE, Western blot, ELISA, and alpha1-PI activity assays enabled us to select the transformant(s) secreting a biologically active glycosylated r-alpha1-PI with yields of up to 12 mg/L. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) analysis further confirmed that molecular mass of the r-alpha1-PI was similar to that of the pd-alpha1-PI. In vitro stability of the r-alpha1-PI from A. niger was tested in comparison with pd-alpha1-PI reference and non-glycosylated human r-alpha1-PI from E. coli. CONCLUSION: We examined the suitability of the filamentous fungus A. niger for the expression of the human gene for alpha1-PI, a medium size glycoprotein of high therapeutic value. The heterologous expression of the human gene for alpha1-PI in A. niger was successfully achieved to produce the secreted mature human r-alpha1-PI in A. niger as a biologically active glycosylated protein with improved stability and with yields of up to 12 mg/L in shake-flask growth.

Dimerization of the class A G protein-coupled neurotensin receptor NTS1 alters G protein interaction.

G protein-coupled receptors (GPCRs) have been found as monomers but also as dimers or higher-order oligomers in cells. The relevance of the monomeric or dimeric receptor state for G protein activation is currently under debate for class A rhodopsin-like GPCRs. Clarification of this issue requires the availability of well defined receptor preparations as monomers or dimers and an assessment of their ligand-binding and G protein-coupling properties. We show by pharmacological and hydrodynamic experiments that purified neurotensin receptor NTS1, a class A GPCR, dimerizes in detergent solution in a concentration-dependent manner, with an apparent affinity in the low nanomolar range. At low receptor concentrations, NTS1 binds the agonist neurotensin with a Hill slope of approximately 1; at higher receptor concentrations, neurotensin binding displays positive cooperativity with a Hill slope of approximately 2. NTS1 monomers activate G alpha q beta(1)gamma(2), whereas receptor dimers catalyze nucleotide exchange with lower affinity. Our results demonstrate that NTS1 dimerization per se is not a prerequisite for G protein activation.

Extracellular structure of polysialic acid explored by on cell solution NMR.

The capsular polysaccharide of the pathogens Neisseria meningitidis serogroup B and of Escherichia coli K1, alpha(2 --> 8) polysialic acid (PSA), is unusual, because when injected into adult humans, it generates little or no antibody. In contrast, people infected with these pathogens generate specific serum antibodies. A structural study on cells is used to address this anomaly by characterizing antigen structures in vivo. We introduce on cell multidimensional solution NMR spectroscopy for direct observation of PSA on E. coli bacteria. Using 13C,15N-labeled PSA, we applied a combination of heteronuclear NMR methods, such as heteronuclear single quantum coherence, HNCA, and HNCO, in vivo. Analysis reveals that free and cell-bound PSA are structurally similar, indicating that the poor immunogenicity of PSA is not due to major structural differences between cells and purified PSA. The 13C linewidths of PSA on cells are 2 to 3 times larger than the corresponding ones in free PSA. The possible implications of the differences between free and on cell PSA are discussed. In addition, we demonstrate the suitability of the method for in vivo kinetic studies.

Screen-less expanded bed column: new approach for the recovery and purification of a malaria transmission blocking vaccine candidate from Pichia pastoris.

An experimental malaria transmission blocking vaccine antigen, Pfs25H, expressed and secreted from Pichia pastoris was recovered and purified using a screenless expanded bed column equipped with a rotating fluid distribution system. This column was able to accommodate feed stock, containing 30% biomass, at a flow rate of 300-400 cm/h without affecting column stability. This capability is three times higher than the capability of the expanded bed column currently in use, which is equipped with a perforated plate fluid distribution system; this design could accommodate biomass concentrations of only up to 10%. The screen-less design did not affect the binding capacity, purification level or process yield and, therefore, shorten the process. Purified Pfs25H of 6.4 g were recovered from 37 l of Pichia pastoris culture in one step.

Large-scale expression and purification of a G-protein-coupled receptor for structure determination -- an overview.

Structure determination of G-protein-coupled receptors and other applications, such as nuclear magnetic resonance studies, require milligram quantities of purified, functional receptor protein on a regular basis. We present an overview on expression and purification studies with a receptor for neurotensin. Functional expression in Escherichia coli and an automated two-column purification routine allow ongoing crystallization experiments and studies on receptor-bound ligands.

The beginnings of mucin biosynthesis: the crystal structure of UDP-GalNAc:polypeptide alpha-N-acetylgalactosaminyltransferase-T1.

UDP-GalNAc:polypeptide alpha-N-acetylgalactosaminyltransferases (ppGaNTases) initiate the formation of mucin-type, O-linked glycans by catalyzing the transfer of alpha-N-acetylgalactosamine from UDP-GalNAc to Ser or Thr residues of core proteins to form the Tn antigen (GalNAc-alpha-1-O-Ser/Thr). ppGaNTases are unique among glycosyltransferases in containing a C-terminal lectin domain. We present the x-ray crystal structure of a ppGaNTase, murine ppGaNTase-T1, and show that it folds to form distinct catalytic and lectin domains. The association of the two domains forms a large cleft in the surface of the enzyme that contains a Mn2+ ion complexed by invariant D209 and H211 of the "DXH" motif and by invariant H344. Each of the three potential lectin domain carbohydrate-binding sites (alpha, beta, and gamma) is located on the active-site face of the enzyme, suggesting a mechanism by which the transferase may accommodate multiple conformations of glycosylated acceptor substrates. A model of a mucin 1 glycopeptide substrate bound to the enzyme shows that the spatial separation between the lectin alpha site and a modeled active site UDP-GalNAc is consistent with the in vitro pattern of glycosylation observed for this peptide catalyzed by ppGaNTase-T1. The structure also provides a template for the larger ppGaNTase family, and homology models of several ppGaNTase isoforms predict dramatically different surface chemistries consistent with isoform-selective acceptor substrate recognition.

Automated large-scale purification of a G protein-coupled receptor for neurotensin.

Structure determination of integral membrane proteins requires milligram amounts of purified, functional protein on a regular basis. Here, we describe a protocol for the purification of a G protein-coupled neurotensin receptor fusion protein at the 3-mg or 10-mg level using immobilized metal affinity chromatography and a neurotensin column in a fully automated mode. Fermentation at a 200-l scale of Escherichia coli expressing functional receptors provides the material needed to feed into the purification routine. Constructs with tobacco etch virus protease recognition sites at either end of the receptor allow the isolation of neurotensin receptor devoid of its fusion partners. The presented expression and purification procedures are simple and robust, and provide the basis for crystallization experiments of receptors on a routine basis.