Bacterial glycoprofiling by using random sequence peptide microarrays

Selection of a de novo gene that can promote survival of Escherichia coli by modulating protein homeostasis pathways

Cellular novelty can emerge when non-functional loci become functional genes in a process termed de novo gene birth. But how proteins with random amino acid sequences beneficially integrate into existing cellular pathways remains poorly understood. We screened ~108 genes, generated from random nucleotide sequences and devoid of homology to natural genes, for their ability to rescue growth arrest of Escherichia coli cells producing the ribonuclease toxin MazF. We identified ~2,000 genes that could promote growth, probably by reducing transcription from the promoter driving toxin expression. Additionally, one random protein, named Random antitoxin of MazF (RamF), modulated protein homeostasis by interacting with chaperones, leading to MazF proteolysis and a consequent loss of its toxicity. Finally, we demonstrate that random proteins can improve during evolution by identifying beneficial mutations that turned RamF into a more efficient inhibitor. Our work provides a mechanistic basis for how de novo gene birth can produce functional proteins that effectively benefit cells evolving under stress.

The Origins and Functions of De Novo Genes: Against All Odds?

"De novo" genes evolve from previously non-genic DNA. This strikes many of us as remarkable, because it seems extraordinarily unlikely that random sequence would produce a functional gene. How is this possible? In this two-part review, I first summarize what is known about the origins and molecular functions of the small number of de novo genes for which such information is available. I then speculate on what these examples may tell us about how de novo genes manage to emerge despite what seem like enormous opposing odds.

Scoping review of the applications of peptide microarrays on the fight against human infections

INTRODUCTION

This scoping review explores the use of peptide microarrays in the fight against infectious diseases. The research domains explored included the use of peptide microarrays in the mapping of linear B-cell and T cell epitopes, antimicrobial peptide discovery, immunosignature characterisation and disease immunodiagnostics. This review also provides a short overview of peptide microarray synthesis.

METHODS

Electronic databases were systematically searched to identify relevant studies. The review was conducted using the Joanna Briggs Institute methodology for scoping reviews and data charting was performed using a predefined form. The results were reported by narrative synthesis in line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews guidelines.

RESULTS

Ninety-five articles from 103 studies were included in the final data charting process. The majority (92. 0%) of the articles were published during 2010-2020 and were mostly from Europe (44.2%) and North America (34.7%). The findings were from the investigation of viral (45.6%), bacterial (32. 0%), parasitic (23.3%) and fungal (2. 0%) infections. Out of the serological studies, IgG was the most reported antibody type followed by IgM. The largest portion of the studies (77.7%) were related to mapping B-cell linear epitopes, 5.8% were on diagnostics, 5.8% reported on immunosignature characterisation and 8.7% reported on viral and bacterial cell binding assays. Two studies reported on T-cell epitope profiling.

CONCLUSION

The most important application of peptide microarrays was found to be B-cell epitope mapping or antibody profiling to identify diagnostic and vaccine targets. Immunosignatures identified by random peptide microarrays were found to be applied in the diagnosis of infections and interrogation of vaccine responses. The analysis of the interactions of random peptide microarrays with bacterial and viral cells using binding assays enabled the identification of antimicrobial peptides. Peptide microarray arrays were also used for T-cell linear epitope mapping which may provide more information for the design of peptide-based vaccines and for the development of diagnostic reagents.

Previously Unrecognized Nonreproducible Antibody-Probe Interactions

Antibody-antigen (Ab-Ag) interactions are canonically described by a model that exclusively accommodates noninteraction (0) or reproducible interaction (RI) states, yet this model is inadequate to explain often-encountered nonreproducible signals. Here, by monitoring diverse experimental systems using a peptide-protein hybrid microarray, we observed that Ab-probe interactions comprise a substantial proportion of nonreproducible antibody-based results. This enabled our discovery and capacity to reliably identify nonreproducible Ab-probe interactions (NRIs), as well as our development of a powerful explanatory model ("0-NRI-RI-Hook four-state model") that is mAb concentration-dependent, regardless of specificity, which ultimately shows that both nonspecific interactions and NRIs are not predictable yet certain to happen. Our discoveries challenge the centrality of Ab-Ag interaction specificity data in serology and immunology.

Rational identification and characterisation of peptide ligands for targeting polysialic acid

The alpha-2,8-linked form of the polysaccharide polysialic acid (PSA) has widespread implications in physiological and pathological processes, ranging from neurological development to disease progression. Though the high electronegativity and excluded volume of PSA often promotes interference of biomolecular interactions, PSA-binding ligands have important implications for both biological processes and biotechnological applications. As such, the design, identification, and characterisation of novel ligands towards PSA is critical for expanding knowledge of PSA interactions and achieving selective glycan targeting. Here, we report on a rational approach for the identification of alpha-2,8-PSA-binding peptides, involving design from the endogenous ligand Siglec-11 and multi-platform characterisation of peptide binding. Microarray-based examination of peptides revealed charge and sequence characteristics influencing peptide affinity to PSA, and carbohydrate-peptide binding was further quantified with a novel fluorescence anisotropy assay. PSA-binding peptides exhibited specific binding to polymeric SA, as well as different degrees of selective binding in various conditions, including competition with PSA of alternating 2,8/9-linkages and screening with PSA-expressing cells. A computational study of Siglec-11 and Siglec-11-derived peptides offered synergistic insight into ligand binding. These results demonstrate the potential of PSA-binding peptides for selective targeting and highlight the importance of the approaches described herein for the study of carbohydrate interactions.

Laboratory Diagnosis of Human Brucellosis

The clinical presentation of brucellosis in humans is variable and unspecific, and thus, laboratory corroboration of the diagnosis is essential for the patient's proper treatment. The diagnosis of brucellar infections can be made by culture, serological tests, and nucleic acid amplification assays. Modern automated blood culture systems enable detection of acute cases of brucellosis within the routine 5- to 7-day incubation protocol employed in clinical microbiology laboratories, although a longer incubation and performance of blind subcultures may be needed for protracted cases. Serological tests, though they lack specificity and provide results that may be difficult to interpret in individuals repeatedly exposed to Brucella organisms, nevertheless remain a diagnostic cornerstone in resource-poor countries. Nucleic acid amplification assays combine exquisite sensitivity, specificity, and safety and enable rapid diagnosis of the disease. However, long-term persistence of positive molecular test results in patients that have apparently fully recovered is common and has unclear clinical significance and therapeutic implications. Therefore, as long as there are no sufficiently validated commercial tests or studies that demonstrate an adequate interlaboratory reproducibility of the different homemade PCR assays, cultures and serological methods will remain the primary tools for the diagnosis and posttherapeutic follow-up of human brucellosis.

Microarrays for the screening and identification of carbohydrate-binding peptides

The development of carbohydrate-binding ligands is crucial for expanding knowledge on the glycocode and for achieving systematic carbohydrate targeting. Amongst such ligands, carbohydrate-binding peptides (CBPs) are attractive for use in bioanalytical and biomedical systems due to their biochemical and physicochemical properties; moreover, given the biological significance of lectin-carbohydrate interactions, these ligands offer an opportunity to study peptide sequence and binding characteristics to inform on natural target/ligand interactions. Here, a high-throughput microarray screening technique is described for the identification and study of CBPs, with a focus on polysialic acid (PSA), a polysaccharide found on neural stem cells. The chemical and biological uniqueness of PSA suggests that an ability to exclusively target this glycan may promote a number of diagnostic and therapeutic applications. PSA-binding peptides from phage display screening and from epitope mapping of an scFv for oligosialic acid were screened in an optimized microarray format with three ligand density conditions. Hypothesis-driven mutations were additionally applied to select peptides to modulate peptide affinity and selectivity to PSA. Peptide compositional and positional analyses revealed the significance of various residues for PSA binding and suggested the importance of basic residue positioning for PSA recognition. Furthermore, selectivity studies performed directly on microarrays with chondroitin sulfate A (CS-A) demonstrated the value of screening for both affinity and selectivity in the development of CBPs. Thus, the integrated approach described, with attention to design strategy, screening, and peptide characterization, successfully identified novel PSA-binding ligands and offers a platform for the identification and study of additional polysaccharide-binding peptides.

Identification of non-random sequence properties in groups of signature peptides obtained in random sequence peptide microarray experiments

Immunosignaturing is an emerging experimental technique that uses random sequence peptide microarrays to detect antibodies produced by the immune system in response to a particular disease. Two important questions regarding immunosignaturing are "Do microarray peptides that exhibit a strong affinity to a given type of antibodies share common sequence properties?" and "If so, what are those properties?" In this work, three statistical tests designed to detect non-random patterns in the amino acid makeup of a group of microarray peptides are presented. One test detects patterns of significantly biased amino acid usage, whereas the other two detect patterns of significant bias in the biochemical properties. These tests do not require a large number of peptides per group. The tests were applied to analyze 19 groups of peptides identified in immunosignaturing experiments as being specific for antibodies produced in response to various types of cancer and other diseases. The positional distribution of the biochemical properties of the amino acids in these 19 peptide groups was also studied. Remarkably, despite the random nature of the sequence libraries used to design the microarrays, a unique group-specific non-random pattern was identified in the majority of the peptide groups studied. © 2016 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 318-329, 2016.

Diagnosis and early detection of CNS-SLE in MRL/lpr mice using peptide microarrays

Background

An accurate method that can diagnose and predict lupus and its neuropsychiatric manifestations is essential since currently there are no reliable methods. Autoantibodies to a varied panel of antigens in the body are characteristic of lupus. In this study we investigated whether serum autoantibody binding patterns on random-sequence peptide microarrays (immunosignaturing) can be used for diagnosing and predicting the onset of lupus and its central nervous system (CNS) manifestations. We also tested the techniques for identifying potentially pathogenic autoantibodies in CNS-Lupus. We used the well-characterized MRL/lpr lupus animal model in two studies as a first step to develop and evaluate future studies in humans.

Results

In study one we identified possible diagnostic peptides for both lupus and altered behavior in the forced swim test. When comparing the results of study one to that of study two (carried out in a similar manner), we further identified potential peptides that may be diagnostic and predictive of both lupus and altered behavior in the forced swim test. We also characterized five potentially pathogenic brain-reactive autoantibodies, as well as suggested possible brain targets.

Conclusions

These results indicate that immunosignaturing could predict and diagnose lupus and its CNS manifestations. It can also be used to characterize pathogenic autoantibodies, which may help to better understand the underlying mechanisms of CNS-Lupus.

Nanoengineered glycan sensors enabling native glycoprofiling for medicinal applications: towards profiling glycoproteins without labeling or liberation steps

Nanoengineered glycan sensors may help realize the long-held goal of accurate and rapid glycoprotein profiling without labeling or glycan liberation steps. Current methods of profiling oligosaccharides displayed on protein surfaces, such as liquid chromatography, mass spectrometry, capillary electrophoresis, and microarray methods, are limited by sample pretreatment and quantitative accuracy. Microarrayed platforms can be improved with methods that better estimate kinetic parameters rather than simply reporting relative binding information. These quantitative glycan sensors are enabled by an emerging class of nanoengineered materials that differ in their mode of signal transduction from traditional methods. Platforms that respond to mass changes include a quartz crystal microbalance and cantilever sensors. Electronic response can be detected from electrochemical, field effect transistor, and pore impedance sensors. Optical methods include fluorescent frontal affinity chromatography, surface plasmon resonance methods, and fluorescent carbon nanotubes. After a very brief primer on glycobiology and its connection to medicine, these emerging systems are critically reviewed for their potential use as core sensors in future glycoprofiling tools.

Binding sugars: from natural lectins to synthetic receptors and engineered neolectins

The large diversity and complexity of glycan structures together with their crucial role in many biological or pathological processes require the development of new high-throughput techniques for analyses. Lectins are classically used for characterising, imaging or targeting glycoconjugates and, when printed on microarrays, they are very useful tools for profiling glycomes. Development of recombinant lectins gives access to reliable and reproducible material, while engineering of new binding sites on existing scaffolds allows tuning of specificity. From the accumulated knowledge on protein-carbohydrate interactions, it is now possible to use nucleotide and peptide (bio)synthesis for producing new carbohydrate-binding molecules. Such a biomimetic approach can also be addressed by boron chemistry and supra-molecular chemistry for the design of fully artificial glycosensors.

A technology for developing synbodies with antibacterial activity

The rise in antibiotic resistance has led to an increased research focus on discovery of new antibacterial candidates. While broad-spectrum antibiotics are widely pursued, there is evidence that resistance arises in part from the wide spread use of these antibiotics. Our group has developed a system to produce protein affinity agents, called synbodies, which have high affinity and specificity for their target. In this report, we describe the adaptation of this system to produce new antibacterial candidates towards a target bacterium. The system functions by screening target bacteria against an array of 10,000 random sequence peptides and, using a combination of membrane labeling and intracellular dyes, we identified peptides with target specific binding or killing functions. Binding and lytic peptides were identified in this manner and in vitro tests confirmed the activity of the lead peptides. A peptide with antibacterial activity was linked to a peptide specifically binding Staphylococcus aureus to create a synbody with increased antibacterial activity. Subsequent tests showed that this peptide could block S. aureus induced killing of HEK293 cells in a co-culture experiment. These results demonstrate the feasibility of using the synbody system to discover new antibacterial candidate agents.

Deciphering enzyme function using peptide arrays

Enzymes are key molecules in signal-transduction pathways. However, only a small fraction of more than 500 human kinases, 300 human proteases and 200 human phosphatases is characterised so far. Peptide microarray based technologies for extremely efficient profiling of enzyme substrate specificity emerged in the last years. This technology reduces set-up time for HTS assays and allows the identification of downstream targets. Moreover, peptide microarrays enable optimisation of enzyme substrates. Focus of this review is on assay principles for measuring activities of kinases, phosphatases or proteases and on substrate identification/optimisation for kinases. Additionally, several examples for reliable identification of substrates for lysine methyl-transferases, histone deacetylases and SUMO-transferases are given. Finally, use of high-density peptide microarrays for the simultaneous profiling of kinase activities in complex biological samples like cell lysates or lysates of complete organisms is described. All published examples of peptide arrays used for enzyme profiling are summarised comprehensively.

Evaluation of biological sample preparation for immunosignature-based diagnostics

To address the need for a universal system to assess health status, we previously described a method termed "immunosignaturing" which splays the entire humoral antibody repertoire across a peptide microarray. Two important issues relative to the potential broad use of immunosignatures are sample preparation and stability. In the present study, we compared the immunosignatures developed from serum, plasma, saliva, and antibodies eluted from blood dried onto filter paper. We found that serum and plasma provide identical immunosignatures. Immunosignatures derived from dried blood also correlated well with those from nondried serum from the same individual. Immunosignatures derived from dried blood were capable of distinguishing naïve mice from those infected with influenza virus. Saliva was applied to the arrays, and the IgA immunosignature correlated strongly with that from dried blood. Finally, we demonstrate that dried blood retains immunosignature information even when exposed to high temperature. This work expands the potential diagnostic uses for immunosignatures. These features suggest that different forms of archival samples can be used for diagnosis development and that in prospective studies samples can be easily procured.

High-throughput platform for rapid deployment of antimicrobial agents

A new approach to conducting bacterial binding assays by using an addressable high density random sequence peptide microarray is described. When bacterial binding is carried out in the presence of a competing excess of corresponding bacterial lipopolysaccharide (LPS), most of the observed bacterial binding is inhibited, suggesting that LPS is the major target of the bacterial binding peptides. Importantly, the amino acid composition of the selected peptides closely resembles the composition of natural antimicrobial peptides. Conjugation of selected peptides to polyvalent nanoparticle scaffold yields constructs that show potent antibacterial agglutination activities. The system is general enough to potentially create antimicrobial agents to virtually any pathogen.

Application of immunosignatures to the assessment of Alzheimer's disease

OBJECTIVE

Accurate assessment of Alzheimer's disease (AD), both presymptomatically and at different disease stages, will become increasingly important with the expanding elderly population. There are a number of indications that the immune system is engaged in AD. Here we explore the ability of an antibody-profiling technology to characterize AD and screen for peptides that may be used for a simple diagnostic test.

METHODS

We developed an array-based system to profile the antibody repertoire of transgenic mice with cerebral amyloidosis (TG) and elderly individuals with or without AD. The array consists of 10,000 random sequence peptides (20-mers) capable of detecting antibody binding patterns, allowing the identification of peptides that mimic epitopes targeted by a donor's serum.

RESULTS

TG mice exhibited a distinct immunoprofile compared to nontransgenic littermates. Further, we show that dementia patients, including autopsy-confirmed AD subjects, have distinguishable profiles compared to age-matched nondemented people. Using antibodies to different forms of Aβ peptide and blocking protocols, we demonstrate that most of this signature is not due to the subject's antibodies raised against Aβ.

INTERPRETATION

We propose that "immunosignaturing" technology may have potential as a diagnostic tool in AD.

Glycobiomimics and glycobiosensors

Following steady advances in analytical technologies, our knowledge in glycomics is now increasing rapidly. Over the last decade, specific glycans have been described that are associated with a range of diseases, such as cancer and inflammation, with host-pathogen interactions and with various stages during stem cell development and differentiation. Simultaneously, deeper structural insight has been gained on glycosylated biopharmaceutical protein therapeutics manufactured in CHO (Chinese-hamster ovary) and other cell systems. This glycomic information is highly relevant for clinicians and biomanufacturing industries as a new class of glycobiomarkers emerges. However, current methods of glycoanalysis are primarily research tools and are not suitable for point-of-care on-site detection and analysis, or sensor devices. Lectin-based glycan detection provides the most promising approach to fill these gaps. However, the limited availability of lectins with high specificity and sensitivity for specific glycan motifs presents one of the main challenges in building reliable glycobiosensors. Recent reports have demonstrated the use of recombinant protein engineering, phage display and aptamer technologies in the production of lectin mimics, as well as the construction of biosensors that are capable of rapidly detecting glycan motifs at low levels in both a labelled and label-free manner. These are primarily proof-of-principle reports at this stage, but some of the approaches, either alone or in combination, will lead to functional glycobiosensors in the coming years which will be valuable tools for the clinical, biopharmaceutical and life science research communities.

Exploring antibody recognition of sequence space through random-sequence peptide microarrays

A universal platform for efficiently mapping antibody epitopes would be of great use for many applications, ranging from antibody therapeutic development to vaccine design. Here we tested the feasibility of using a random peptide microarray to map antibody epitopes. Although peptide microarrays are physically constrained to ∼10(4) peptides per array, compared with 10(8) permitted in library panning approaches such as phage display, they enable a much more high though put and direct measure of binding. Long (20 mer) random sequence peptides were chosen for this study to look at an unbiased sampling of sequence space. This sampling of sequence space is sparse, as an exact epitope sequence is unlikely to appear. Commercial monoclonal antibodies with known linear epitopes or polyclonal antibodies raised against engineered 20-mer peptides were used to evaluate this array as an epitope mapping platform. Remarkably, peptides with the most sequence similarity to known epitopes were only slightly more likely to be recognized by the antibody than other random peptides. We explored the ability of two methods singly and in combination to predict the actual epitope from the random sequence peptides bound. Though the epitopes were not directly evident, subtle motifs were found among the top binding peptides for each antibody. These motifs did have some predictive ability in searching for the known epitopes among a set of decoy sequences. The second approach using a windowing alignment strategy, was able to score known epitopes of monoclonal antibodies well within the test dataset, but did not perform as well on polyclonals. Random peptide microarrays of even limited diversity may serve as a useful tool to prioritize candidates for epitope mapping or antigen identification.

The evolvability of lead peptides from small library screens

Very little is known about the evolvability of lead peptides that are isolated from small library screens. Here we begin to explore this question by comparing the directed evolution of two peptides previously isolated from a small library screen to new ligands generated de novo by in vitro selection.

A general method for characterization of humoral immunity induced by a vaccine or infection

A universal system to diagnose disease, characterize infection or evaluate the response to a vaccine would be useful. Towards this end we introduce a machine-readable platform that we term "Immunosignaturing". Rather than attempt to identify antibodies one by one, we splay the entire immune response across an array of 10,000 random sequence peptides. This segregates serum antibodies sufficiently to group and characterize responses caused by disease or vaccination. In the present study, we explore in detail the murine immunosignature to influenza A/PR/8/34 immunization and subsequent challenge. Even though the peptides are random sequence, the response to immunization and challenge is quite apparent. We find that the immunosignatures contained information not evident in whole virus ELISA. Antibody recognition of 283 influenza-specific peptides increased upon immunization and remained elevated for 211 days post-challenge. A set of 65 peptides, which overlapped 39 of the peptides that were consistent across time, was capable of distinguishing mice based on infectious dose, while whole virus ELISA could not. These peptide populations are consistently recognized in independent biological replicates of infection and are largely, but not solely, composed of virus reactive antibodies. The immunosignaturing analysis was expanded to analysis of human recipients of the 2006/2007 seasonal influenza vaccine. We find that 30 peptides are significantly recognized by all donors 21 days post-immunization and have the power to distinguish immune from pre-immune samples. Taken together the data suggest that immunosignaturing on a random peptide array can serve as a universal platform to assess antibody status in ways that cannot be replicated by conventional immunological assays.

Never take candy from a stranger: the role of the bacterial glycome in host–pathogen interactions

With the comprehensive study and complete sequencing of the Haemophilus influenzae genome in 1995 came the term ‘genomics’ and the beginning of the ‘omics’ era. Since this time, several analogous fields, such as transcriptomics and proteomics, have emerged. While growth and advancement in these fields have increased understanding of microbial virulence, the study of bacterial glycomes is still in its infancy and little is known concerning their role in host–pathogen interactions. Bacterial glycomics is challenging owing to the diversity of glyco-conjugate molecules, vast array of unusual sugars and limited number of analytical approaches available. However, recent advances in glycomics technologies offer the potential for exploration and characterization of both the structures and functions of components of bacterial glycomes in a systematic manner. Such characterization is a prerequisite for discerning the role of bacterial glycans in the interaction between host defences and bacterial virulence factors.