Enabling Lipidomic Biomarker Studies for Protected Populations by Combining Noninvasive Fingerprint Sampling with MS Analysis and Machine Learning.

Triacylglycerols and wax esters are two lipid classes that have been linked to diseases, including autism, Alzheimer's disease, dementia, cardiovascular disease, dry eye disease, and diabetes, and thus are molecules worthy of biomarker exploration studies. Since triacylglycerols and wax esters make up the majority of skin-surface lipid secretions, a viable sampling method for these potential biomarkers would be that of groomed latent fingerprints. Currently, however, blood-based sampling protocols predominate in the field. The invasiveness of a blood draw limits its utility to protected populations, including children and the elderly. Herein we describe a noninvasive means for sample collection (from fingerprints) paired with fast MS data-acquisition (MassIVE data set MSV000092742) and efficient data analysis via machine learning. Using both supervised and unsupervised classification, we demonstrate the usefulness of this method in determining whether a variable of interest imparts measurable change within the lipidomic data set. As a proof-of-concept, we show that the method is capable of distinguishing between the fingerprints of different individuals as well as between anatomical sebum collection regions. This noninvasive, high-throughput approach enables future lipidomic biomarker researchers to more easily include underrepresented, protected populations, such as children and the elderly, thus moving the field closer to definitive disease diagnoses that apply to all.

Asymmetric conformations of cleaved HIV-1 envelope glycoprotein trimers in styrene-maleic acid lipid nanoparticles.

During virus entry, the pretriggered human immunodeficiency virus (HIV-1) envelope glycoprotein (Env) trimer initially transits into a default intermediate state (DIS) that remains structurally uncharacterized. Here, we present cryo-EM structures at near-atomic resolution of two cleaved full-length HIV-1 Env trimers purified from cell membranes in styrene-maleic acid lipid nanoparticles without antibodies or receptors. The cleaved Env trimers exhibited tighter subunit packing than uncleaved trimers. Cleaved and uncleaved Env trimers assumed remarkably consistent yet distinct asymmetric conformations, with one smaller and two larger opening angles. Breaking conformational symmetry is allosterically coupled with dynamic helical transformations of the gp41 N-terminal heptad repeat (HR1N) regions in two protomers and with trimer tilting in the membrane. The broken symmetry of the DIS potentially assists Env binding to two CD4 receptors-while resisting antibody binding-and promotes extension of the gp41 HR1 helical coiled-coil, which relocates the fusion peptide closer to the target cell membrane.

Advances, obstacles, and opportunities for machine learning in proteomics.

The fields of proteomics and machine learning are both large disciplines, each producing well over 5,000 publications per year. However, studies combining both fields are still relatively rare, with only about 2% of recent proteomics papers including machine learning. This review, which focuses on the intersection of the fields, is intended to inspire proteomics researchers to develop skills and knowledge in the application of machine learning. A brief tutorial introduction to machine learning is provided, and research advances that rely on both fields, particularly as they relate to proteomics tools development and biomarker discovery, are highlighted. Key knowledge gaps and opportunities for scientific advancement are also enumerated.

The Skin and Gut Microbiome in Hidradenitis Suppurativa: Current Understanding and Future Considerations for Research and Treatment.

Hidradenitis suppurativa (HS) is a chronic, inflammatory skin disease comprising painful abscesses, deep nodules, fistulas, and scarring predominantly in the axilla and groin. Bacterial colonization of HS lesions has been well characterized and may lead to chronic infection of lesions. While disease pathogenesis of HS is not fully understood, there is increasing evidence that microbial dysbiosis may be occurring in numerous locations, including the skin and gut. The skin-gut microbiome has been proposed as a mechanism by which inflammatory skin disorders, including HS, can be exacerbated. This is evidenced by HS patients being significantly more likely to develop inflammatory bowel disease as well as the well documented cutaneous manifestations in inflammatory bowel disease. In this review, we discuss the current literature regarding HS skin and gut microbiome research. Furthermore, we discuss further considerations for microbiome research in HS, including the potential role of bacterial metabolites in disease progression and future therapeutic avenues like probiotics.

Mass Spectrometry-Based Disulfide Mapping of Lysyl Oxidase-like 2.

Lysyl oxidase-like 2 (LOXL2) catalyzes the oxidative deamination of peptidyl lysines and hydroxylysines to promote extracellular matrix remodeling. Aberrant activity of LOXL2 has been associated with organ fibrosis and tumor metastasis. The lysine tyrosylquinone (LTQ) cofactor is derived from Lys653 and Tyr689 in the amine oxidase domain via post-translational modification. Based on the similarity in hydrodynamic radius and radius of gyration, we recently proposed that the overall structures of the mature LOXL2 (containing LTQ) and the precursor LOXL2 (no LTQ) are very similar. In this study, we conducted a mass spectrometry-based disulfide mapping analysis of recombinant LOXL2 in three forms: a full-length LOXL2 (fl-LOXL2) containing a nearly stoichiometric amount of LTQ, Δ1-2SRCR-LOXL2 (SRCR1 and SRCR2 are truncated) in the precursor form, and Δ1-3SRCR-LOXL2 (SRCR1, SRCR2, SRCR3 are truncated) in a mixture of the precursor and the mature forms. We detected a set of five disulfide bonds that is conserved in both the precursor and the mature recombinant LOXL2s. In addition, we detected a set of four alternative disulfide bonds in low abundance that is not associated with the mature LOXL2. These results suggest that the major set of five disulfide bonds is retained post-LTQ formation.

Predicting undernutrition among elementary schoolchildren in the Philippines using machine learning algorithms.

OBJECTIVES: This study aimed to compare the accuracy of four machine-learning (ML) algorithms, using two classification schemes, to predict undernutrition based on individual and household risk factors. METHODS: Data on public-school children were collected from a rural province (310 children) and a highly urbanized city (308 children) in the Philippines using 24-h dietary recalls and a household socioeconomic and demographic survey. Children's nutritional risk was classified based on acceptable macronutrient distribution ranges (AMDRs) developed by the National Academy of Medicine (NAM) and Philippine Dietary Reference Intakes (PDRIs). Four algorithms (random forest, support-vector machine, linear discriminant analysis, and logistic regression) predicted undernutrition in the sample, and their accuracy, sensitivity, and specificity were compared. Predictions were also compared with the national school feeding program's anthropometric classifications. RESULTS: The prevalence of undernutrition was greater under NAM AMDRs (82.67%) compared with PDRI AMDRs (78.71%). Random forest was the most accurate ML algorithm (78.55%), able to predict undernutrition based on household expenditures, child and household age, food insecurity, and dietary diversity. Compared with anthropometric classification (213 children), AMDRs classified more children as at risk for inadequate dietary intake (477 children). CONCLUSIONS: The random forest algorithm performed best in predicting undernutrition among Filipino elementary schoolchildren, although results could be improved with bootstrap aggregation. The AMDR classification shows potential for targeting feeding beneficiaries. However, local dietary culture should be considered in the development of nutrition interventions. Government use of big-data techniques such as ML must also address underrepresentation in health data collected from and accessible to poor populations or risk further marginalizing them.

Analysis of Glycosylation and Disulfide Bonding of Wild-Type SARS-CoV-2 Spike Glycoprotein.

The SARS-CoV-2 coronavirus, the etiologic agent of COVID-19, uses its spike (S) glycoprotein anchored in the viral membrane to enter host cells. The S glycoprotein is the major target for neutralizing antibodies elicited by natural infection and by vaccines. Approximately 35% of the SARS-CoV-2 S glycoprotein consists of carbohydrate, which can influence virus infectivity and susceptibility to antibody inhibition. We found that virus-like particles produced by coexpression of SARS-CoV-2 S, M, E, and N proteins contained spike glycoproteins that were extensively modified by complex carbohydrates. We used a fucose-selective lectin to purify the Golgi-modified fraction of a wild-type SARS-CoV-2 S glycoprotein trimer and determined its glycosylation and disulfide bond profile. Compared with soluble or solubilized S glycoproteins modified to prevent proteolytic cleavage and to retain a prefusion conformation, more of the wild-type S glycoprotein N-linked glycans are processed to complex forms. Even Asn 234, a significant percentage of which is decorated by high-mannose glycans on other characterized S trimer preparations, is predominantly modified in the Golgi compartment by processed glycans. Three incompletely occupied sites of O-linked glycosylation were detected. Viruses pseudotyped with natural variants of the serine/threonine residues implicated in O-linked glycosylation were generally infectious and exhibited sensitivity to neutralization by soluble ACE2 and convalescent antisera comparable to that of the wild-type virus. Unlike other natural cysteine variants, a Cys15Phe (C15F) mutant retained partial, but unstable, infectivity. These findings enhance our understanding of the Golgi processing of the native SARS-CoV-2 S glycoprotein carbohydrates and could assist the design of interventions. IMPORTANCE The SARS-CoV-2 coronavirus, which causes COVID-19, uses its spike glycoprotein to enter host cells. The viral spike glycoprotein is the main target of host neutralizing antibodies that help to control SARS-CoV-2 infection and are important for the protection provided by vaccines. The SARS-CoV-2 spike glycoprotein consists of a trimer of two subunits covered with a coat of carbohydrates (sugars). Here, we describe the disulfide bonds that assist the SARS-CoV-2 spike glycoprotein to assume the correct shape and the composition of the sugar moieties on the glycoprotein surface. We also evaluate the consequences of natural virus variation in O-linked sugar addition and in the cysteine residues involved in disulfide bond formation. This information can expedite the improvement of vaccines and therapies for COVID-19.

Asymmetric Structures and Conformational Plasticity of the Uncleaved Full-Length Human Immunodeficiency Virus Envelope Glycoprotein Trimer.

The functional human immunodeficiency virus (HIV-1) envelope glycoprotein (Env) trimer [(gp120/gp41)3] is produced by cleavage of a conformationally flexible gp160 precursor. gp160 cleavage or the binding of BMS-806, an entry inhibitor, stabilizes the pretriggered, "closed" (state 1) conformation recognized by rarely elicited broadly neutralizing antibodies. Poorly neutralizing antibodies (pNAbs) elicited at high titers during natural infection recognize more "open" Env conformations (states 2 and 3) induced by binding the receptor, CD4. We found that BMS-806 treatment and cross-linking decreased the exposure of pNAb epitopes on cell surface gp160; however, after detergent solubilization, cross-linked and BMS-806-treated gp160 sampled non-state-1 conformations that could be recognized by pNAbs. Cryo-electron microscopy of the purified BMS-806-bound gp160 revealed two hitherto unknown asymmetric trimer conformations, providing insights into the allosteric coupling between trimer opening and structural variation in the gp41 HR1N region. The individual protomer structures in the asymmetric gp160 trimers resemble those of other genetically modified or antibody-bound cleaved HIV-1 Env trimers, which have been suggested to assume state-2-like conformations. Asymmetry of the uncleaved Env potentially exposes surfaces of the trimer to pNAbs. To evaluate the effect of stabilizing a state-1-like conformation of the membrane Env precursor, we treated cells expressing wild-type HIV-1 Env with BMS-806. BMS-806 treatment decreased both gp160 cleavage and the addition of complex glycans, implying that gp160 conformational flexibility contributes to the efficiency of these processes. Selective pressure to maintain flexibility in the precursor of functional Env allows the uncleaved Env to sample asymmetric conformations that potentially skew host antibody responses toward pNAbs. IMPORTANCE The envelope glycoprotein (Env) trimers on the surface of human immunodeficiency virus (HIV-1) mediate the entry of the virus into host cells and serve as targets for neutralizing antibodies. The functional Env trimer is produced by cleavage of the gp160 precursor in the infected cell. We found that the HIV-1 Env precursor is highly plastic, allowing it to assume different asymmetric shapes. This conformational plasticity is potentially important for Env cleavage and proper modification by sugars. Having a flexible, asymmetric Env precursor that can misdirect host antibody responses without compromising virus infectivity would be an advantage for a persistent virus like HIV-1.

The opportunity cost of automated glycopeptide analysis: case study profiling the SARS-CoV-2 S glycoprotein.

Glycosylation analysis of viral glycoproteins contributes significantly to vaccine design and development. Among other benefits, glycosylation analysis allows vaccine developers to assess the impact of construct design or producer cell line choices for vaccine production, and it is a key measure by which glycoproteins that are produced for use in vaccination can be compared to their native viral forms. Because many viral glycoproteins are multiply glycosylated, glycopeptide analysis is a preferrable approach for mapping the glycans, yet the analysis of glycopeptide data can be cumbersome and requires the expertise of an experienced analyst. In recent years, a commercial software product, Byonic, has been implemented in several instances to facilitate glycopeptide analysis on viral glycoproteins and other glycoproteomics data sets, and the purpose of the study herein is to determine the strengths and limitations of using this software, particularly in cases relevant to vaccine development. The glycopeptides from a recombinantly expressed trimeric S glycoprotein of the SARS-CoV-2 virus were first analyzed using an expert-based analysis strategy; subsequently, analysis of the same data set was completed using Byonic. Careful assessment of instances where the two methods produced different results revealed that the glycopeptide assignments from Byonic contained more false positives than true positives, even when the data were assessed using a 1% false discovery rate. The work herein provides a roadmap for removing the spurious assignments that Byonic generates, and it provides an assessment of the opportunity cost for relying on automated assignments for glycopeptide data sets from viral glycoproteins.

Analysis of glycosylation and disulfide bonding of wild-type SARS-CoV-2 spike glycoprotein.

The SARS-CoV-2 coronavirus, the etiologic agent of COVID-19, uses its spike (S) glycoprotein anchored in the viral membrane to enter host cells. The S glycoprotein is the major target for neutralizing antibodies elicited by natural infection and by vaccines. Approximately 35% of the SARS-CoV-2 S glycoprotein consists of carbohydrate, which can influence virus infectivity and susceptibility to antibody inhibition. We found that virus-like particles produced by coexpression of SARS-CoV-2 S, M, E and N proteins contained spike glycoproteins that were extensively modified by complex carbohydrates. We used a fucose-selective lectin to enrich the Golgi-resident fraction of a wild-type SARS-CoV-2 S glycoprotein trimer, and determined its glycosylation and disulfide bond profile. Compared with soluble or solubilized S glycoproteins modified to prevent proteolytic cleavage and to retain a prefusion conformation, more of the wild-type S glycoprotein N-linked glycans are processed to complex forms. Even Asn 234, a significant percentage of which is decorated by high-mannose glycans on soluble and virion S trimers, is predominantly modified in the Golgi by processed glycans. Three incompletely occupied sites of O-linked glycosylation were detected. Viruses pseudotyped with natural variants of the serine/threonine residues implicated in O-linked glycosylation were generally infectious and exhibited sensitivity to neutralization by soluble ACE2 and convalescent antisera comparable to that of the wild-type virus. Unlike other natural cysteine variants, a Cys15Phe (C15F) mutant retained partial, but unstable, infectivity. These findings enhance our understanding of the Golgi processing of the native SARS-CoV-2 S glycoprotein carbohydrates and could assist the design of interventions.

Analysis of glycosylation and disulfide bonding of wild-type SARS-CoV-2 spike glycoprotein

The SARS-CoV-2 coronavirus, the etiologic agent of COVID-19, uses its spike (S) glycoprotein anchored in the viral membrane to enter host cells. The S glycoprotein is the major target for neutralizing antibodies elicited by natural infection and by vaccines. Approximately 35% of the SARS-CoV-2 S glycoprotein consists of carbohydrate, which can influence virus infectivity and susceptibility to antibody inhibition. We found that virus-like particles produced by coexpression of SARS-CoV-2 S, M, E and N proteins contained spike glycoproteins that were extensively modified by complex carbohydrates. We used a fucose-selective lectin to enrich the Golgi-resident fraction of a wild-type SARS-CoV-2 S glycoprotein trimer, and determined its glycosylation and disulfide bond profile. Compared with soluble or solubilized S glycoproteins modified to prevent proteolytic cleavage and to retain a prefusion conformation, more of the wild-type S glycoprotein N-linked glycans are processed to complex forms. Even Asn 234, a significant percentage of which is decorated by high-mannose glycans on soluble and virion S trimers, is predominantly modified in the Golgi by processed glycans. Three incompletely occupied sites of O-linked glycosylation were detected. Viruses pseudotyped with natural variants of the serine/threonine residues implicated in O-linked glycosylation were generally infectious and exhibited sensitivity to neutralization by soluble ACE2 and convalescent antisera comparable to that of the wild-type virus. Unlike other natural cysteine variants, a Cys15Phe (C15F) mutant retained partial, but unstable, infectivity. These findings enhance our understanding of the Golgi processing of the native SARS-CoV-2 S glycoprotein carbohydrates and could assist the design of interventions.

High level stable expression of recombinant HIV gp120 in glutamine synthetase gene deficient HEK293T cells.

Due to the important pathological roles of the HIV-1 gp120, the protein has been intensively used in the research of HIV. However, recombinant gp120 preparation has proven to be difficult because of extremely low expression levels. In order to facilitate gp120 expression, previous methods predominantly involved the replacement of native signal peptide with a heterologous one, resulting in very limited improvement. Currently, preparation of recombinant gp120 with native glycans relies solely on transient expression systems, which are not amendable for large scale production. In this work, we employed a different approach for gp120 expression. Besides replacing the native gp120 signal peptide with that of rat serum albumin and optimizing its codon usage, we generated a stable gp120-expressing cell line in a glutamine synthetase knockout HEK293T cell line that we established for the purpose of amplification of recombinant gene expressions. The combined usage of these techniques dramatically increased gp120 expression levels and yielded a functional product with human cell derived glycan. This method may be applicable to large scale preparation of other viral envelope proteins, such as that of the emerging SARS-CoV-2, or other glycoproteins which require the presence of authentic human glycans.

Selective ozone activation of phenanthrene in liquid CO2.

We demonstrate liquid CO2 (8 °C, 4.4 MPa) as a benign medium to perform safe ozonolysis of phenanthrene at near-ambient temperatures. The ozonolysis products consist of several monomeric oxidation products such as diphenaldehyde, diphenic acid and phenanthrenequinone as well as polymeric structures up to 1130 Da. The observed chemical shifts (1H-6.03 ppm, 13C-104.38 ppm) in 2D-NMR spectra of the products confirm the formation of secondary ozonide. Based on the range of observed products, a Criegee-type mechanism is proposed. The ability to deconstruct phenanthrene and produce oxygenated precursors via this technique is particularly of interest in creating new materials from aromatic moieties.

Clinically Viable Assay for Monitoring Uromodulin Glycosylation.

Uromodulin, also known as the Tamm-Horsfall protein or THP, is the most abundant protein excreted in human urine. It is associated with the progression of kidney diseases; therefore, changes in the glycosylation profile of this protein could serve as a potential biomarker for kidney health. The typical glycomics analysis approaches used to quantify uromodulin glycosylation involve time-consuming and tedious glycoprotein isolation and labeling steps, which limit their utility in clinical glycomics assays, where sample throughput is important. Herein, we introduce a radically simplified sample preparation workflow, with direct ESI-MS analysis, enabling the quantification of N-linked glycans that originate from uromodulin. The method omits any glycan labeling steps but includes steps to reduce the salt content of the samples, thereby minimizing ion suppression. The method is effective for quantifying subtle glycosylation differences of uromodulin samples derived from different biological states. As a proof of concept, glycosylation from samples that differ by pregnancy status were shown to be differentiable.

PRADA: Portable Reusable Accurate Diagnostics with nanostar Antennas for multiplexed biomarker screening.

Precise monitoring of specific biomarkers in biological fluids with accurate biodiagnostic sensors is critical for early diagnosis of diseases and subsequent treatment planning. In this work, we demonstrated an innovative biodiagnostic sensor, portable reusable accurate diagnostics with nanostar antennas (PRADA), for multiplexed biomarker detection in small volumes (~50 µl) enabled in a microfluidic platform. Here, PRADA simultaneously detected two biomarkers of myocardial infarction, cardiac troponin I (cTnI), which is well accepted for cardiac disorders, and neuropeptide Y (NPY), which controls cardiac sympathetic drive. In PRADA immunoassay, magnetic beads captured the biomarkers in human serum samples, and gold nanostars (GNSs) "antennas" labeled with peptide biorecognition elements and Raman tags detected the biomarkers via surface-enhanced Raman spectroscopy (SERS). The peptide-conjugated GNS-SERS barcodes were leveraged to achieve high sensitivity, with a limit of detection (LOD) of 0.0055 ng/ml of cTnI, and a LOD of 0.12 ng/ml of NPY comparable with commercially available test kits. The innovation of PRADA was also in the regeneration and reuse of the same sensor chip for ~14 cycles. We validated PRADA by testing cTnI in 11 de-identified cardiac patient samples of various demographics within a 95% confidence interval and high precision profile. We envision low-cost PRADA will have tremendous translational impact and be amenable to resource-limited settings for accurate treatment planning in patients.

Antigenicity and Immunogenicity of HIV-1 Envelope Trimers Complexed to a Small-Molecule Viral Entry Inhibitor.

Small-molecule viral entry inhibitors, such as BMS-626529 (BMS-529), allosterically block CD4 binding to HIV-1 envelope (Env) and inhibit CD4-induced structural changes in Env trimers. Here, we show that the binding of BMS-529 to clade C soluble chimeric gp140 SOSIP (ch.SOSIP) and membrane-bound trimers with intact transmembrane domain (gp150) prevented trimer conformational transitions and enhanced their immunogenicity. When complexed to BMS-529, ch.SOSIP trimers retained their binding to broadly neutralizing antibodies (bNAbs) and to their unmutated common ancestor (UCA) antibodies, while exposure of CD4-induced (CD4i) non-bNAb epitopes was inhibited. BMS-529-complexed gp150 trimers in detergent micelles, which were isolated from CHO cells, bound to bNAbs, including UCA and intermediates of the CD4 binding site (bs) CH103 bNAb lineage, and showed limited exposure of CD4i epitopes and a glycosylation pattern with a preponderance of high-mannose glycans. In rabbits, BMS-529-complexed V3 glycan-targeting ch.SOSIP immunogen induced in the majority of immunized animals higher neutralization titers against both autologous and select high mannose-bearing heterologous tier 2 pseudoviruses than those immunized with the noncomplexed ch.SOSIP. In rhesus macaques, BMS-529 complexed to CD4 bs-targeting ch.SOSIP immunogen induced stronger neutralization against tier 2 pseudoviruses bearing high-mannose glycans than noncomplexed ch.SOSIP trimer immunogen. When immunized with gp150 complexed to BMS-529, rhesus macaques showed neutralization against tier 2 pseudoviruses with targeted glycan deletion and high-mannose glycan enrichment. These results demonstrated that stabilization of Env trimer conformation with BMS-529 improved the immunogenicity of select chimeric SOSIP trimers and elicited tier 2 neutralizing antibodies of higher potency than noncomplexed trimers.IMPORTANCE Soluble forms of HIV-1 envelope trimers exhibit conformational heterogeneity and undergo CD4-induced (CD4i) exposure of epitopes of non-neutralizing antibodies that can potentially hinder induction of broad neutralizing antibody responses. These limitations have been mitigated through recent structure-guided approaches and include trimer-stabilizing mutations that resist trimer conformational transition and exposure of CD4i epitopes. The use of small-molecule viral inhibitors that allosterically block CD4 binding represents an alternative strategy for stabilizing Env trimer in the pre-CD4-triggered state of both soluble and membrane-bound trimers. In this study, we report that the viral entry inhibitor BMS-626529 restricts trimer conformational transition and improves the immunogenicity of select Env trimer immunogens.

How to Apply Supervised Machine Learning Tools to MS Imaging Files: Case Study with Cancer Spheroids Undergoing Treatment with the Monoclonal Antibody Cetuximab.

As the field of mass spectrometry imaging continues to grow, so too do its needs for optimal methods of data analysis. One general need in image analysis is the ability to classify the underlying regions within an image, as healthy or diseased, for example. Classification, as a general problem, is often best accomplished by supervised machine learning strategies; unfortunately, conducting supervised machine learning on MS imaging files is not typically done by mass spectrometrists because a high degree of specialized knowledge is needed. To address this problem, we developed a fully open-source approach that facilitates supervised machine learning on MS imaging files, and we demonstrated its implementation on sets of cancer spheroids that either had or had not undergone chemotherapy treatment. These supervised machine learning studies demonstrated that metabolic changes induced by the monoclonal antibody, Cetuximab, are detectable but modest at 24 h, and by 72 h, the drug induces a larger and more diverse metabolic response.

HIV vaccine delayed boosting increases Env variable region 2-specific antibody effector functions.

In the RV144 HIV-1 phase III trial, vaccine efficacy directly correlated with the magnitude of the variable region 2-specific (V2-specific) IgG antibody response, and in the presence of low plasma IgA levels, with the magnitude of plasma antibody-dependent cellular cytotoxicity. Reenrollment of RV144 vaccinees in the RV305 trial offered the opportunity to define the function, maturation, and persistence of vaccine-induced V2-specific and other mAb responses after boosting. We show that the RV144 vaccine regimen induced persistent V2 and other HIV-1 envelope-specific memory B cell clonal lineages that could be identified throughout the approximately 11-year vaccination period. Subsequent boosts increased somatic hypermutation, a critical requirement for antibody affinity maturation. Characterization of 22 vaccine-induced V2-specific mAbs with epitope specificities distinct from previously characterized RV144 V2-specific mAbs CH58 and CH59 found increased in vitro antibody-mediated effector functions. Thus, when inducing non-neutralizing antibodies, one method by which to improve HIV-1 vaccine efficacy may be through late boosting to diversify the V2-specific response to increase the breadth of antibody-mediated anti-HIV-1 effector functions.

The Aristotle Classifier: Using the Whole Glycomic Profile To Indicate a Disease State.

"The totality is not, as it were, a mere heap, but the whole is something besides the parts."-Aristotle. We built a classifier that uses the totality of the glycomic profile, not restricted to a few glycoforms, to differentiate samples from two different sources. This approach, which relies on using thousands of features, is a radical departure from current strategies, where most of the glycomic profile is ignored in favor of selecting a few features, or even a single feature, meant to capture the differences in sample types. The classifier can be used to differentiate the source of the material; applicable sources may be different species of animals, different protein production methods, or, most importantly, different biological states (disease vs healthy). The classifier can be used on glycomic data in any form, including derivatized monosaccharides, intact glycans, or glycopeptides. It takes advantage of the fact that changing the source material can cause a change in the glycomic profile in many subtle ways: some glycoforms can be upregulated, some downregulated, some may appear unchanged, yet their proportion-with respect to other forms present-can be altered to a detectable degree. By classifying samples using the entirety of their glycan abundances, along with the glycans' relative proportions to each other, the "Aristotle Classifier" is more effective at capturing the underlying trends than standard classification procedures used in glycomics, including PCA (principal components analysis). It also outperforms workflows where a single, representative glycomic-based biomarker is used to classify samples. We describe the Aristotle Classifier and provide several examples of its utility for biomarker studies and other classification problems using glycomic data from several sources.