Immunosenescence and novel vaccination strategies for the elderly

Vaccination remains the most effective prophylactic intervention for infectious disease in the healthcare professional’s toolkit. However, the efficacy and effectiveness of vaccines decrease with age. This becomes most apparent after an individual reaches 65-70 years old, and results from complex changes in the immune system that occur during aging. As such, new vaccine formulations and strategies that can accommodate age-related changes in immunity are required to protect this expanding population. Here, we summarize the consequences of immunosenescence on vaccination and how novel vaccination strategies can be designed to accommodate the aging immune system. We conclude that current vaccination protocols are not sufficient to protect our aging population and, in some cases, are an inefficient use of healthcare resources. Researchers and clinicians are developing novel vaccination strategies that include modifying who and when we vaccinate and that capitalize on existing vaccines, in addition to formulating new vaccines specifically tailored to the elderly in order to remedy this deficiency

The role of the cytoplasmic domain of the macrophage scavenger receptor MARCO in adhesion and uptake

The macrophage receptor with collagenous structure (MARCO) is a class A scavenger receptor. Class A scavenger receptors are multifunctional type II transmembrane glycoproteins that have roles in modified lipoprotein uptake, innate immunity, and macrophage adhesion. It has been shown that the extracellular cysteine-rich domain of MARCO is important for ligand binding, but the role of the cytoplasmic N-terminal domain has not yet been characterised. The aim of this study was to investigate the role of the cytoplasmic domain in cell adhesion and motility, ligand binding and uptake. Two truncated forms of human MARCO were used in this study: N- MARCO lacks the entire cytoplasmic domain; Nmyr MARCO includes the membrane-proximal putative myristoylation site, but lacks the rest of the cytoplasmic domain. The constructs were expressed in transiently transfected HEK 293T cells. The Nmyr MARCO mutant had reduced cell surface expression, an effect that was even more apparent in cells transfected with NMARCO. This indicates that the putative myristoylation site is not obligatory for cell surface expression of MARCO, but increases cell surface expression of the protein. When bound to ligand, the two mutants demonstrated a significant increase in cell surface expression, while the cell surface expression of the full-length MARCO remained unchanged. This indicates that the cytoplasmic tail affects membrane trafficking and the regulation of cell surface expression. Maleylated proteins are ligands for scavenger receptor A and other scavenger receptors. This study demonstrates that maleylated bovine serum albumin (MalBSA) is also a ligand for MARCO and this modified protein was used to study MARCO-mediated adhesion and ligand binding. The results show that the cytoplasmic domain of MARCO is not required for binding to MalBSA coated particles. Interestingly, the Nmyr MARCO mutant showed a decreased ability to bind soluble MalBSA compared to the full-length protein indicating that the cytoplasmic domain may be necessary for endocytosis. The cytoplasmic domain of MARCO appeared to be absolutely required for adhesion to tissue culture plastic, anti-MARCO antibody PLK-1 coated surfaces and suspension grade plastic, and a lesser extent to MalBSA coated surfaces. MARCO mediated adhesion was shown not to require the presence of serum and divalent cations. Studies performed with murine primary resident peritoneal macrophages on a MalBSA coated surface indicated that MARCO is responsible for increased chemokinesis. The results of this study show that the cytoplasmic domain of MARCO affects cell surface expression, endocytosis and adhesion. Further research is needed to determine if and how the cytoplasmic domain on MARCO participates in signalling required for these processes and if it affects cell motility.</p

The Evolution of the Scavenger Receptor Cysteine-Rich Domain of the Class A Scavenger Receptors

The class A Scavenger Receptor (cA-SR) family is a group of five evolutionarily related innate immune receptors. The cA-SRs are known for their promiscuous ligand binding; as they have been shown to bind bacteria such as Streptococcus pneumoniae, and Escherichia coli, as well as different modified forms of low-density lipoprotein. Three of the five family members possess a Scavenger Receptor Cysteine Rich (SRCR) domain while the remaining two receptors lack the domain. Previous work has suggested that the Macrophage Associated Receptor with COllagenous structure (MARCO) shares a recent common ancestor with the non-SRCR-containing receptors; however the origin of the SRCR domain within the cA-SRs remains unknown. We hypothesize that the SRCR domains of the cA-SRs have a common origin that predates teleost fish. Using the newly available sequence data from sea lamprey and ghost shark genome projects, we have shown that MARCO shares a common ancestor with the SRCR-containing proteins. In addition, we explored the evolutionary relationships within the SRCR domain by reconstructing the ancestral SRCR domains of the cA-SRs. We identified a motif that is highly conserved between the cA-SR SRCR domains and the ancestral SRCR domain that consist of WGTVCDD. We also show that the GRAEVYY motif, a functionally important motif within MARCO, is poorly conserved in the other cA-SRs and in the reconstructed ancestral domain. Further, we identified three sites within MARCO’s SRCR domain which are under positive selection. Two of these sites lie adjacent to the conserved WGTVCDD motif, and may indicate a potential biological function for these sites. Together these findings indicate a common origin of the SRCR domain within the cA-SRs; however different selective pressures between the proteins may have caused MARCOs SRCR domain to evolve to contain different functional motifs when compared to the other SRCR-containing cA-SRs

An introduction to automated flow cytometry gating tools and their implementation

Current flow cytometry reagents and instrumentation allow for the measurement of an unprecedented number of parameters for any given cell within a homogenous or heterogeneous population. While this provides a great deal of power for hypothesis testing, it also generates a vast amount of data, which is typically analyzed manually through a processing called gating. For large experiments, such as high-content screens, in which many parameters are measured, the time required for manual analysis as well as the technical variability inherent to manual gating can increase dramatically, even becoming prohibitive depending on the clinical or research goal. In the following article, we aim to provide the reader an overview of automated flow cytometry analysis as well as an example of the implementation of FLOCK (FLOw Clustering without K), a tool that we consider accessible to researchers of all levels of computational expertise. In most cases, computational assistance methods are more reproducible and much faster than manual gating, and for some, also allow for the discovery of cellular populations that might not be expected or evident to the researcher. We urge any researcher that is planning or has previously performed large flow cytometry experiments to consider implementing computational assistance into their analysis pipeline

The evolution of the scavenger receptor cysteine-rich domain of the class A scavenger receptors

The class A Scavenger Receptor (cA-SR) family is a group of five evolutionarily related innate immune receptors. The cA-SRs are known for their promiscuous ligand binding; as they have been shown to bind bacteria such as Streptococcus pneumoniae, and Escherichia coli, as well as different modified forms of low-density lipoprotein. Three of the five family members possess a Scavenger Receptor Cysteine Rich (SRCR) domain while the remaining two receptors lack the domain. Previous work has suggested that the Macrophage Associated Receptor with COllagenous structure (MARCO) shares a recent common ancestor with the non-SRCR-containing receptors; however the origin of the SRCR domain within the cA-SRs remains unknown. We hypothesize that the SRCR domains of the cA-SRs have a common origin that predates teleost fish. Using the newly available sequence data from sea lamprey and ghost shark genome projects, we have shown that MARCO shares a common ancestor with the SRCR-containing proteins. In addition, we explored the evolutionary relationships within the SRCR domain by reconstructing the ancestral SRCR domains of the cA-SRs. We identified motif that is highly conserved between the cA-SR SRCR domains and the ancestral SRCR domain that consist of WGTVCDD. We also show that the GRAEVYY motif, a functionally important motif within MARCO, is poorly conserved in the other cA-SRs and in the reconstructed ancestral domain. Further, we identified three sites within MARCO's SRCR domain which are under positive selection. Two of these sites lie adjacent to the conserved WGTVCDD motif, and may indicate a potential biological function for these sites. Together these findings indicate a common origin of the SRCR domain within the cA-SRs; however different selective pressures between the proteins may have caused MARCOs SRCR domain to evolve to contain different functional motifs when compared to the other SRCR-containing cA- SRs.</p

Characterizing amino acid variations of scavenger receptors by class information gain

Conserved amino acids in sequences, which may be discovered as patterns across or along sequences, reveal functional domains within proteins. Conversely, less conserved amino acid sequences reveal areas of evolutionary divergence. Traditional protein classification trains patterns using pre-defined class labels (i.e. information about the input sequences such as gene name or family) in order to predict the class of novel sequences. However, these supervised algorithms may be inherently biased by such class dependent techniques. There- fore, we have created an unsupervised algorithm that is not affected by the inherent errors or class balance biases in the class labels. Our algorithm first discovers statistically significant sequence patterns, then aligns and clusters them into Aligned Pattern Clusters (APCs), which represent con- served amino acid sequences. APCs reveal sequence patterns (horizontal regions of amino acid homology), regions of con- servation (vertical regions of amino acid homology), and re- gions of divergence (areas of vertical amino acid variation) within families of proteins. Finally, the algorithm verifies the results using two measures { class entropy and class in- formation gain { both of which incorporate the class labels. The advantage of our method is that it does not require any a priori knowledge of a protein's structure or function. We applied our unsupervised algorithm to the class A Scavenger Receptor (cA-SR) protein family consisting of two distinct but related proteins, MARCO and SRAI. Using MARCO and SRAI as the class labels, we applied our class measures, class entropy and information gain. We found that class entropy revealed conservation of patterns and amino acids between sequences from all classes. The class information gain indicated which of these amino acids were found distinct to the MARCO class or the SRAI class, which allowed us to make important predictions as to the differing biological functions of these proteins.</p

Partitioning and correlating subgroup characteristics from Aligned Pattern Clusters

Motivation: Evolutionarily conserved amino acids within proteins characterize functional or structural regions. Conversely, less conserved amino acids within these regions are generally areas of evolutionary divergence. A priori knowledge of biological function and species can help interpret the amino acid differences between sequences. However, this information is often erroneous or unavailable, hampering discovery with supervised algorithms. Also, most of the current unsupervised methods depend on full sequence similarity, which become inaccurate when proteins diverge (e.g. inversions, deletions, insertions). Due to these and other shortcomings, we developed a novel unsupervised algorithm which discovers highly conserved regions and uses two types of information measures: (i) data measures computed from input sequences; and (ii) class measures computed using a priori class groupings in order to reveal subgroups (i.e. classes) or functional characteristics. Results: Using known and putative sequences of two proteins belonging to a relatively uncharacterized protein family we were able to group evolutionarily related sequences and identify conserved regions, which are strong homologous association patterns called Aligned Pattern Clusters, within individual proteins and across the members of this family. An initial synthetic demonstration and in silico results reveal that (i) the data measures are unbiased and (ii) our class measures can accurately rank the quality of the evolutionarily relevant groupings. Furthermore, combining our data and class measures allowed us to interpret the results by inferring regions of biological importance within the binding domain of these proteins. Compared to popular supervised methods, our algorithm has a superior runtime and comparable accuracy.</p

A guide to bioinformatics for immunologists

Bioinformatics includes a suite of methods, which are cheap, approachable, and many of which are easily accessible without any sort of specialized bioinformatic training. Yet, despite this, bioinformatic tools are under-utilized by immunologists. Herein, we review a representative set of publicly available, easy-to-use bioinformatic tools using our own research on an under-annotated human gene, SCARA3, as an example. SCARA3 shares an evolutionary relationship with the class A scavenger receptors, but preliminary research showed that it was divergent enough that its function remained unclear. In our quest for more information about this gene - did it share gene sequence similarities to other scavenger receptors? Did it contain conserved protein domains? Where was it expressed in the human body? - we discovered the power and informative potential of publicly available bioinformatic tools designed for the novice in mind, which allowed us to hypothesize on the regulation, structure, and function of this protein. We argue that these tools are largely applicable to many facets of immunology research.</p

The evolution of the class A scavenger receptors.

The class A scavenger receptors are a subclass of a diverse family of proteins defined based on their ability to bind modified lipoproteins. The 5 members of this family are strikingly variable in their protein structure and function, raising the question as to whether it is appropriate to group them as a family based on their ligand binding abilities. To investigate these relationships, we defined the domain architecture of each of the 5 members followed by collecting and annotating class A scavenger receptor mRNA and amino acid sequences from publicly available databases. Phylogenetic analyses, sequence alignments, and permutation tests revealed a common evolutionary ancestry of these proteins, indicating that they form a protein family. We postulate that 4 distinct gene duplication events and subsequent domain fusions, internal repeats, and deletions are responsible for the diverse protein structures and functions of this family. Despite variation in domain structure, there are highly conserved regions across all 5 members, indicating the possibility that these regions may represent key conserved functional motifs. We have shown with significant evidence that the 5 members of the class A scavenger receptors form a protein family. We have indicated that these receptors have a common origin which may provide insight into future functional work with these proteins.</p