Immunological techniques: ELISA, flow cytometry, and immunohistochemistry

OMIC Technologies and Vaccine Development: From the Identification of Vulnerable Individuals to the Formulation of Invulnerable Vaccines

Routine vaccination is among the most effective clinical interventions to prevent diseases as it is estimated to save over 3 million lives every year. However, the full potential of global immunization programs is not realised because population coverage is still suboptimal. This is also due to the inadequate immune response and paucity of informative correlates of protection upon immunization of vulnerable individuals such as newborns, preterm infants, pregnant women, and elderly individuals as well as those patients affected by chronic and immune compromising medical conditions. In addition, these groups are undervaccinated for a number of reasons, including lack of awareness of vaccine-preventable diseases and uncertainty or misconceptions about the safety and efficacy of vaccination by parents and healthcare providers. The presence of these nonresponders/undervaccinated individuals represents a major health and economic burden to society, which will become particularly difficult to address in settings with limited public resources. This review describes innovative and experimental approaches that can help identify specific genomic profiles defining nonresponder individuals for whom specific interventions might be needed. We will provide examples that show how such information can be useful to identify novel biomarkers of safety and immunogenicity for future vaccine trials. Finally, we will discuss how system biology “OMICs” data can be used to design bioinformatic tools to predict the vaccination outcome providing genetic and molecular “signatures” of protective immune response. This strategy may soon enable identification of signatures highly predictive of vaccine safety, immunogenicity, and efficacy/protection thereby informing personalized vaccine interventions in vulnerable populations.

Porphyromonas gingivalis antibody levels and diagnosis of coronary artery disease in HIV-positive individuals

BACKGROUND AND OBJECTIVE

Periodontal disease has been associated with cardiovascular disease in the general population. It is unknown whether IgG antibody levels for periodontal pathogens are associated with the diagnosis of coronary artery disease (CAD) in HIV-positive individuals.

MATERIAL AND METHODS

Twenty-four HIV-positive individuals (cases) with stored plasma available in the 12 months before CAD diagnosis were age- and sex-matched 1:2 with 46 HIV-positive individuals without CAD (controls). Antibody levels to whole cell extracts from periodontal pathogens Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans and Fusobacterium nucleatum, as well as markers of inflammation sCD14, CXCL10 and high-sensitivity C-reactive protein, were compared between cases and controls using enzyme-linked immunosorbent assays.

RESULTS

P. gingivalis-specific IgG levels (μg/mL) were significantly higher in individuals with CAD (median 1.48 [IQR 1.06-2.05]) compared to controls (0.70 [IQR 0.35-1.24], P<.001), and remained significantly higher following adjustment for traditional cardiovascular risk factors and HIV viral load (OR 21.6 [95% CI 3.73-125.63] P=.001). There was a borderline association between A. actinomycetemcomitans IgG antibody levels (cases, median 3.86 [IQR 3.19-4.72]; controls, 3.34 [IQR 2.59-4.07], P=.050) and no association found between F. nucleatum antibody levels and CAD. sCD14 levels (μg/mL) were higher in cases compared with controls (median 3.45 [IQR 3.03-4.11] vs 2.65 [IQR 2.32-2.99] P<.001), while CXCL10 (median 127 pg/mL [IQR 88-157] vs 153 [IQR 90-244] P=.321) and high-sensitivity C-reactive protein (median 3.44 mg/L [1.98-5.32] vs 1.85 [1.13-6.88] P=.203) levels were not different between cases and controls.

CONCLUSION

Periodontal bacteria may be contributing to CAD risk in HIV-positive individuals.

Proven in vitro evolution of protease cathepsin E-inhibitors and -activators at pH 4.5 using a paired peptide method

Improving a particular function of molecules is often more difficult than identifying such molecules ab initio. Here, a method to acquire higher affinity and/or more functional peptides was developed as a progressive library selection method. The primary library selection products were utilized to build a secondary library composed of blocks of 4 amino acids, of which selection led to peptides with increased activity. These peptides were further converted to randomly generate paired peptides. Cathepsin E-inhibitors thus obtained exhibited the highest activities and affinities (pM order). This was also the case with cathepsin E-activating peptides, proving the methodological effectiveness. The primary, secondary, and tertiary library selections can be regarded as module-finding, module-shuffling, and module-pairing, respectively, which resembles the progression of the natural evolution of proteins. The mode of peptide binding to their target proteins is discussed in analogy to antibodies and epitopes of an antigen.