Mimotopes selected with neutralizing antibodies against multiple subtypes of influenza A

Background

The mimotopes of viruses are considered as the good targets for vaccine design. We prepared mimotopes against multiple subtypes of influenza A and evaluate their immune responses in flu virus challenged Balb/c mice.

Methods

The mimotopes of influenza A including pandemic H1N1, H3N2, H2N2 and H1N1 swine-origin influenza virus were screened by peptide phage display libraries, respectively. These mimotopes were engineered in one protein as multi- epitopes in Escherichia coli (E. coli) and purified. Balb/c mice were immunized using the multi-mimotopes protein and specific antibody responses were analyzed using hemagglutination inhibition (HI) assay and enzyme-linked immunosorbent assay (ELISA). The lung inflammation level was evaluated by hematoxylin and eosin (HE).

Results

Linear heptopeptide and dodecapeptide mimotopes were obtained for these influenza virus. The recombinant multi-mimotopes protein was a 73 kDa fusion protein. Comparing immunized infected groups with unimmunized infected subsets, significant differences were observed in the body weight loss and survival rate. The antiserum contained higher HI Ab titer against H1N1 virus and the lung inflammation level were significantly decreased in immunized infected groups.

Conclusions

Phage-displayed mimotopes against multiple subtypes of influenza A were accessible to the mouse immune system and triggered a humoral response to above virus.

     

Apoptosis,cytokine and chemokine induction by non-structural 1 (NS1) proteins encoded by different influenza subtypes

Background

Influenza pandemic remains a serious threat to human health. Viruses of avian origin, H5N1, H7N7 and H9N2, have repeatedly crossed the species barrier to infect humans. Recently, a novel strain originated from swine has evolved to a pandemic. This study aims at improving our understanding on the pathogenic mechanism of influenza viruses, in particular the role of non-structural (NS1) protein in inducing pro-inflammatory and apoptotic responses.

Methods

Human lung epithelial cells (NCI-H292) was used as an in-vitro model to study cytokine/chemokine production and apoptosis induced by transfection of NS1 mRNA encoded by seven infleunza subtypes (seasonal and pandemic H1, H2, H3, H5, H7, and H9), respectively.

Results

The results showed that CXCL-10/IP10 was most prominently induced (> 1000 folds) and IL-6 was slightly induced (< 10 folds) by all subtypes. A subtype-dependent pattern was observed for CCL-2/MCP-1, CCL3/MIP-1α, CCL-5/RANTES and CXCL-9/MIG; where induction by H5N1 was much higher than all other subtypes examined. All subtypes induced a similar temporal profile of apoptosis following transfection. The level of apoptosis induced by H5N1 was remarkably higher than all others. The cytokine/chemokine and apoptosis inducing ability of the 2009 pandemic H1N1 was similar to previous seasonal strains.

Conclusions

In conclusion, the NS1 protein encoded by H5N1 carries a remarkably different property as compared to other avian and human subtypes, and is one of the keys to its high pathogenicity. NCI-H292 cells system proves to be a good in-vitro model to delineate the property of NS1 proteins.

     

Expression pattern of NLRP3 and its related cytokines in the lung and brain of avian influenza virus H9N2 infected BALB/c mice

Background

H9N2 avian influenza virus (AIV) becomes the focus for its ability of transmission to mammals and as a donor to provide internal genes to form the new epidemic lethal influenza viruses. Residue 627 in PB2 has been proven the virulence factor of H9N2 avian influenza virus in mice, but the detailed data for inflammation difference between H9N2 virus strains with site 627 mutation is still unclear. The inflammasome NLRP3 is recently reported as the cellular machinery responsible for activation of inflammatory processes and plays an important role during the development of inflammation caused by influenza virus infection.

Methods

In this study, we investigated the expression pattern of NLRP3 and its related cytokines of IL-1β and TNF-α in BALB/c mice infected by H9N2 AIV strains with only a site 627 difference at both mRNA and protein levels at different time points.

Results

The results showed that the expression level of NLRP3, IL-1β and TNF-α changed in the lung and brain of BALB/c mice after infection by V_K627 and rV_K627E. The immunohistological results showed that the positive cells of NLRP3, IL-1β and TNF-α altered the positive levels of original cells in tissues and infiltrated inflammatory cells which caused by H9N2 infection.

Conclusions

Our results provided the basic data at differences in expression pattern of NLRP3 and its related cytokines in BALB/c mice infected by H9N2 influenza viruses with only a site 627 difference. This implied that NLRP3 inflammasome plays a role in host response to influenza virus infection and determines the outcome of clinical manifestation and pathological injury. This will explain the variable of pathological presentation in tissues and enhance research on inflammation process of the AIV H9N2 infection.

     

re-TAMD: exploring interactions between H3 peptide and YEATS domain using enhanced sampling

Background

Analysis of preferred binding regions of a ligand on a protein is important for detecting cryptic binding pockets and improving the ligand selectivity.

Result

The enhanced sampling approach TAMD has been adapted to allow a ligand to unbind from its native binding site and explore the protein surface. This so-called re-TAMD procedure was then used to explore the interaction between the N terminal peptide of histone H3 and the YEATS domain. Depending on the length of the peptide, several regions of the protein surface were explored. The peptide conformations sampled during the re-TAMD correspond to peptide free diffusion around the protein surface.

Conclusions

The re-TAMD approach permitted to get information on the relative influence of different regions of the N terminal peptide of H3 on the interaction between H3 and YEATS.

     

A context-free encoding scheme of protein sequences for predicting antigenicity of diverse influenza A viruses

Background

The evolution of influenza A viruses leads to the antigenic changes. Serological diagnosis of the antigenicity is usually labor-intensive, time-consuming and not suitable for early-stage detection. Computational prediction of the antigenic relationship between emerging and old strains of influenza viruses using viral sequences can facilitate large-scale antigenic characterization, especially for those viruses requiring high biosafety facilities, such as H5 and H7 influenza A viruses. However, most computational models require carefully designed subtype-specific features, thereby being restricted to only one subtype.

Methods

In this paper, we propose a Context-FreeEncoding Scheme (CFreeEnS) for pairs of protein sequences, which encodes a protein sequence dataset into a numeric matrix and then feeds the matrix into a downstream machine learning model. CFreeEnS is not only free from subtype-specific selected features but also able to improve the accuracy of predicting the antigenicity of influenza. Since CFreeEnS is subtype-free, it is applicable to predicting the antigenicity of diverse influenza subtypes, hopefully saving the biologists from conducting serological assays for highly pathogenic strains.

Results

The accuracy of prediction on each subtype tested (A/H1N1, A/H3N2, A/H5N1, A/H9N2) is over 85%, and can be as high as 91.5%. This outperforms existing methods that use carefully designed subtype-specific features. Furthermore, we tested the CFreeEnS on the combined dataset of the four subtypes. The accuracy reaches 84.6%, much higher than the best performance 75.1% reported by other subtype-free models, i.e. regional band-based model and residue-based model, for predicting the antigenicity of influenza. Also, we investigate the performance of CFreeEnS when the model is trained and tested on different subtypes (i.e. transfer learning). The prediction accuracy using CFreeEnS is 84.3% when the model is trained on the A/H1N1 dataset and tested on the A/H5N1, better than the 75.2% using a regional band-based model.

Conclusions

The CFreeEnS not only improves the prediction of antigenicity on datasets with only one subtype but also outperforms existing methods when tested on a combined dataset with four subtypes of influenza viruses.

     

Genetic mutations in influenza H3N2 viruses from a 2012 epidemic in Southern China

Background

An influenza H3N2 epidemic occurred throughout Southern China in 2012.

Methods

We analyzed the hemagglutinin (HA) and neuraminidase (NA) genes of influenza H3N2 strains isolated between 2011–2012 from Guangdong. Mutation sites, evolutionary selection, antigenic sites, and N-glycosylation within these strains were analyzed.

Results

The 2011–2012 Guangdong strains contained the HA-A214S, HA-V239I, HA-N328S, NA-L81P, and NA-D93G mutations, similar to those seen in the A/ Perth/16/2009 influenza strain. The HA-NSS_061–063 and NNS_160–162 glycosylation sites were prevalent among the 2011–2012 Guangdong strains but the NA-NRS_402–404 site was deleted. Antigenically, there was a four-fold difference between A/Perth/16/2009 -like strains and the 2011–2012 Guangdong strains.

Conclusion

Antigenic drift of the H3N2 subtype contributed to the occurrence of the Southern China influenza epidemic of 2012.

     

Application of recombinant hemagglutinin proteins as alternative antigen standards for pandemic influenza vaccines

Objectives

The single radial immunodiffusion (SRID) assay, used to quantify hemagglutinin (HA) in influenza vaccines, requires reference reagents; however, because centralized production of reference reagents may slow the emergency deployment of vaccines, alternatives are needed.

Results

We investigated the production of HA proteins using recombinant DNA technology, rather than a traditional egg-based production process. The HA proteins were then used in an SRID assay as a reference antigen. We found that HA can be quantified in both egg-based and cell-based influenza vaccines when recombinant HAs (rHAs) are used as the reference antigen. Furthermore, we confirmed that rHAs obtained from strains with pandemic potential, such as H5N1, H7N3, H7N9, and H9N2 strains, can be utilized in the SRID assay. The rHA production process takes just one month, in contrast to the traditional process that takes three to four months.

Conclusions

The use of rHAs may reduce the time required to produce reference reagents and facilitate timely introduction of vaccines during emergencies.

     

Identification of cancer subtypes from single-cell RNA-seq data using a consensus clustering method

Background

Human cancers are complex ecosystems composed of cells with distinct molecular signatures. Such intratumoral heterogeneity poses a major challenge to cancer diagnosis and treatment. Recent advancements of single-cell techniques such as scRNA-seq have brought unprecedented insights into cellular heterogeneity. Subsequently, a challenging computational problem is to cluster high dimensional noisy datasets with substantially fewer cells than the number of genes.

Methods

In this paper, we introduced a consensus clustering framework conCluster, for cancer subtype identification from single-cell RNA-seq data. Using an ensemble strategy, conCluster fuses multiple basic partitions to consensus clusters.

Results

Applied to real cancer scRNA-seq datasets, conCluster can more accurately detect cancer subtypes than the widely used scRNA-seq clustering methods. Further, we conducted co-expression network analysis for the identified melanoma subtypes.

Conclusions

Our analysis demonstrates that these subtypes exhibit distinct gene co-expression networks and significant gene sets with different functional enrichment.

     

Antibody responses to intradermal or intramuscular MF59-adjuvanted influenza vaccines as evaluated in elderly institutionalized volunteers during a season of partial mismatching between vaccine and circulating A(H3N2) strains

Background

The age-related weakening of the immune system makes elderly subjects less responsive to influenza vaccination. In the last years, two “enhanced vaccines” were licensed for individuals aged ≥65 years, one being a subunit vaccine (Fluad®) containing the MF59 adjuvant administered intramuscularly (IM-MF59) and the other one a split non-adjuvanted vaccine administered intradermally (Intanza® 15mcg) (ID). In the present study, we evaluated and compared the antibody responses against the three vaccine antigens and heterovariant A(H3N2) circulating viruses induced by IM-MF59 and ID influenza vaccines in 80 elderly institutionalized volunteers (40 per group) during the Winter season 2011–2012.

Results

Hemagglutination inhibiting (HI) antibody titers were assessed in blood samples collected before, 1 and 6 months after vaccination. One month after vaccination both the IM-MF59 and ID vaccines induced increases in HI titers against all the three vaccine strains. The results in the two groups were similar against the A(H3N2) and A(H1N1) strains. Responses against the B strain typically tended to be higher after ID than IM-MF59, yet both vaccines stimulated lower responses against the B strain than against the two A strains. The two vaccines induced favorable results also against four epidemic drifted A(H3N2) viruses circulating in Winter 2011–2012. Six months after vaccination, the HI titers decreased in both groups.

Conclusion

The responses induced by IM-MF59 and ID vaccines in institutionalized elderly people were similar against the A(H3N2) and A(H1N1) strains but frequently higher, for the ID, against the B strain. The two vaccines induced positive responses against drifted A(H3N2) circulating viruses.

     

Research on the relationship between fibrinogen level and subtypes of the TOAST criteria in the acute ischemic stroke

Background

Cerebral infarction caused by different reasons seems differ in fibrinogen levels, so the current work intends to explore the relationship between the fibrinogen level and subtypes of the TOAST criteria in the acute stage of ischemic stroke.

Methods

A total of 577 case research objects were treated acute ischemic stroke patients in our hospital from December 2008 to December 2010, and blood samples within 72 hours of the onset were processed with the fibrinogen (PT-der) measurement. Classification of selected patients according to the TOAST Criteria was conducted to study the distribution of fibrinogen levels in the stroke subtypes.

Results

The distribution of fibrinogen levels in the subtypes was observed to be statistically insignificant.

Conclusions

In the acute stage of ischemic stroke, fibrinogen level was not related to the subtypes of the TOAST criteria.

     

Computational analysis of the receptor binding specificity of novel influenza A/H7N9 viruses

Background

Influenza viruses are undergoing continuous and rapid evolution. The fatal influenza A/H7N9 has drawn attention since the first wave of infections in March 2013, and raised more grave concerns with its increased potential to spread among humans. Experimental studies have revealed several host and virulence markers, indicating differential host binding preferences which can help estimate the potential of causing a pandemic. Here we systematically investigate the sequence pattern and structural characteristics of novel influenza A/H7N9 using computational approaches.

Results

The sequence analysis highlighted mutations in protein functional domains of influenza viruses. Molecular docking and molecular dynamics simulation revealed that the hemagglutinin (HA) of A/Taiwan/1/2017(H7N9) strain enhanced the binding with both avian and human receptor analogs, compared with the previous A/Shanghai/02/2013(H7N9) strain. The Molecular Mechanics - Poisson Boltzmann Surface Area (MM-PBSA) calculation revealed the change of residue-ligand interaction energy and detected the residues with conspicuous binding preference.

Conclusion

The results are novel and specific to the emerging influenza A/Taiwan/1/2017(H7N9) strain compared with A/Shanghai/02/2013(H7N9). Its enhanced ability to bind human receptor analogs, which are abundant in the human upper respiratory tract, may be responsible for the recent outbreak. Residues showing binding preference were detected, which could facilitate monitoring the circulating influenza viruses.

     

Automated metabolite identification from biological fluid <Superscript>1</Superscript>H NMR spectra

Introduction

Metabolite identification in biological samples using Nuclear Magnetic Resonance (NMR) spectra is a challenging task due to the complexity of the biological matrices.

Objectives

This paper introduces a new, automated computational scheme for the identification of metabolites in 1D ¹H NMR spectra based on the Human Metabolome Database.

Methods

The methodological scheme comprises of the sequential application of preprocessing, data reduction, metabolite screening and combination selection.

Results

The proposed scheme has been tested on the 1D ¹H NMR spectra of: (a) an amino acid mixture, (b) a serum sample spiked with the amino acid mixture, (c) 20 blood serum, (d) 20 human amniotic fluid samples, (e) 160 serum samples from publicly available database. The methodological scheme was compared against widely used software tools, exhibiting good performance in terms of correct assignment of the metabolites.

Conclusions

This new robust scheme accomplishes to automatically identify peak resonances in ¹H-NMR spectra with high accuracy and less human intervention with a wide range of applications in metabolic profiling.

     

Oral vaccine of <Emphasis Type="Italic">Lactococcus lactis</Emphasis> harbouring pandemic H1N1 2009 haemagglutinin1 and nisP anchor fusion protein elevates anti-HA1 sIgA levels in mice

Objective

An oral lactococcal-based vaccine which haboured the haemagglutinin1 (HA1) antigen fused to nisP anchor protein for the purpose of surface displaying the HA1 antigen was developed against H1N1 virus.

Results

Recombinant L. lactis strains expressed HA1-nisP fusion proteins when induced with nisin, as confirmed through western blotting. However, immunofluorescense did not detect any surface-displayed proteins, suggesting that the protein was either unsuccessfully translocated or improperly displayed. Despite this, oral administration of recombinant L. lactis strains to BALB/c mice revealed that significant levels of anti-HA1 sIgA antibodies were detected in mice fecal suspension samples of mice group NZ9000 (pNZ:HN) when compared to the negative control NZ9000 (pNZ8048) group.

Conclusion

Specific anti-HA1 sIgA antibodies were locally produced and live recombinant lactococcal vaccine was able to elicit humoral response of BALB/c mice despite unsuccessful surface display of the HA1 epitope.

     

Characterization of ankylosing spondylitis and rheumatoid arthritis using <Superscript>1</Superscript>H NMR-based metabolomics of human fecal extracts

Introduction

The differences in fecal metabolome between ankylosing spondylitis (AS)/rheumatoid arthritis (RA) patients and healthy individuals could be the reason for an autoimmune disorder.

Objectives

The study explored the fecal metabolome difference between AS/RA patients and healthy controls to clarify human immune disturbance.

Methods

Fecal samples from 109 individuals (healthy controls 34, AS 40, and RA 35) were analyzed by ¹H NMR spectroscopy. Data were analyzed with principal component analysis (PCA) and orthogonal projection to latent structure discriminant (OPLS-DA) analysis.

Results

Significant differences in the fecal metabolic profiles could distinguish AS/RA patients from healthy controls but could not distinguish between AS and RA patients. The significantly decreased metabolites in AS/RA patients were butyrate, propionate, methionine, and hypoxanthine. Significantly increased metabolites in AS/RA patients were taurine, methanol, fumarate, and tryptophan.

Conclusion

The metabolome variations in feces indicated AS and RA were two homologous diseases that could not be distinguished by ¹H NMR metabolomics.

     

Comparison between MDCK and MDCK-SIAT1 cell lines as preferred host for cell culture-based influenza vaccine production

Objectives

To evaluate MDCK and MDCK-SIAT1 cell lines for their ability to produce the yield of influenza virus in different Multiplicities of Infection.

Results

Yields obtained for influenza virus H1N1 grown in MDCK-SIAT1 cell was almost the same as MDCK; however, H3N2 virus grown in MDCK-SIAT1 had lower viral titers in comparison with MDCK cells. The optimized MOIs to infect the cells on plates and microcarrier were selected 0.01 and 0.1 for H1N1 and 0.001 and 0.01 for H3N2, respectively.

Conclusions

MDCK-SIAT1 cells may be considered as an alternative mean to manufacture cell-based flu vaccine, especially for the human strains (H1N1), due to its antigenic stability and high titer of influenza virus production.

     

Respiratory failure presenting in H1N1 influenza with Legionnaires disease: two case reports

Introduction

Media sensationalism on the H1N1 outbreak may have influenced decisional processes and clinical diagnosis.

Case Presentation

We report two cases of patients who presented in 2009 with coexisting H1N1 virus and Legionella infections: a 69-year-old Caucasian man and a 71-year-old Caucasian woman. In our cases all the signs and symptoms, including vomiting, progressive respiratory disease leading to respiratory failure, refractory hypoxemia, leukopenia, lymphopenia, thrombocytopenia, and elevated levels of creatine kinase and hepatic aminotransferases, were consistent with critical illness due to 2009 H1N1 virus infection. Other infectious disorders may mimic H1N1 viral infection especially Legionnaires' disease. Because the swine flu H1N1 pandemic occurred in Autumn in Italy, Legionnaires disease was to be highly suspected since the peak incidence usually occurs in early fall. We do think that our immediate suspicion of Legionella infection based on clinical history and X-ray abnormalities was fundamental for a successful resolution.

Conclusion

Our two case reports suggest that patients with H1N1 should be screened for Legionella, which is not currently common practice. This is particularly important since the signs and symptoms of both infections are similar.

     

ASICS: an automatic method for identification and quantification of metabolites in complex 1D <Superscript>1</Superscript>H NMR spectra

Introduction

Experiments in metabolomics rely on the identification and quantification of metabolites in complex biological mixtures. This remains one of the major challenges in NMR/mass spectrometry analysis of metabolic profiles. These features are mandatory to make metabolomics asserting a general approach to test a priori formulated hypotheses on the basis of exhaustive metabolome characterization rather than an exploratory tool dealing with unknown metabolic features.

Objectives

In this article we propose a method, named ASICS, based on a strong statistical theory that handles automatically the metabolites identification and quantification in proton NMR spectra.

Methods

A statistical linear model is built to explain a complex spectrum using a library containing pure metabolite spectra. This model can handle local or global chemical shift variations due to experimental conditions using a warping function. A statistical lasso-type estimator identifies and quantifies the metabolites in the complex spectrum. This estimator shows good statistical properties and handles peak overlapping issues.

Results

The performances of the method were investigated on known mixtures (such as synthetic urine) and on plasma datasets from duck and human. Results show noteworthy performances, outperforming current existing methods.

Conclusion

ASICS is a completely automated procedure to identify and quantify metabolites in ¹H NMR spectra of biological mixtures. It will enable empowering NMR-based metabolomics by quickly and accurately helping experts to obtain metabolic profiles.

     

The first detection of influenza in the Finnish pig population: a retrospective study

Background

Swine influenza is an infectious acute respiratory disease of pigs caused by influenza A virus. We investigated the time of entry of swine influenza into the Finnish pig population. We also describe the molecular detection of two types of influenza A (H1N1) viruses in porcine samples submitted in 2009 and 2010.This retrospective study was based on three categories of samples: blood samples collected for disease monitoring from pigs at major slaughterhouses from 2007 to 2009; blood samples from pigs in farms with a special health status taken in 2008 and 2009; and diagnostic blood samples from pigs in farms with clinical signs of respiratory disease in 2008 and 2009.The blood samples were tested for influenza A antibodies with an antibody ELISA. Positive samples were further analyzed for H1N1, H3N2, and H1N2 antibodies with a hemagglutination inhibition test.Diagnostic samples for virus detection were subjected to influenza A M-gene-specific real-time RT-PCR and to pandemic influenza A H1N1-specific real-time RT-PCR. Positive samples were further analyzed with RT-PCRs designed for this purpose, and the PCR products were sequenced and sequences analyzed phylogenetically.

Results

In the blood samples from pigs in special health class farms producing replacement animals and in diagnostic blood samples, the first serologically positive samples originated from the period July–August 2008. In samples collected for disease monitoring, < 0.1%, 0% and 16% were positive for antibodies against influenza A H1N1 in the HI test in 2007, 2008, and 2009, respectively.Swine influenza A virus of avian-like H1N1 was first detected in diagnostic samples in February 2009. In 2009 and 2010, the avian-like H1N1 virus was detected on 12 and two farms, respectively. The pandemic H1N1 virus (A(H1N1)pdm09) was detected on one pig farm in 2009 and on two farms in 2010.

Conclusions

Based on our study, swine influenza of avian-like H1N1 virus was introduced into the Finnish pig population in 2008 and A(H1N1)pdm09 virus in 2009. The source of avian-like H1N1 infection could not be determined. Cases of pandemic H1N1 in pigs coincided with the period when the A(H1N1)pdm09 virus was spread in humans in Finland.