An evolution-based high-fidelity method of epistasis measurement: Theory and application to influenza

Linkage effects in a multi-locus population strongly influence its evolution. The models based on the traveling wave approach enable us to predict the average speed of evolution and the statistics of phylogeny. However, predicting statistically the evolution of specific sites and pairs of sites in the multi-locus context remains a mathematical challenge. In particular, the effects of epistasis, the interaction of gene regions contributing to phenotype, is difficult to predict theoretically and detect experimentally in sequence data. A large number of false-positive interactions arises from stochastic linkage effects and indirect interactions, which mask true epistatic interactions. Here we develop a proof-of-principle method to filter out false-positive interactions. We start by demonstrating that the averaging of haplotype frequencies over multiple independent populations is necessary but not sufficient for epistatic detection, because it still leaves high numbers of false-positive interactions. To compensate for the residual stochastic noise, we develop a three-way haplotype method isolating true interactions. The fidelity of the method is confirmed analytically and on simulated genetic sequences evolved with a known epistatic network. The method is then applied to a large sequence database of neurominidase protein of influenza A H1N1 obtained from various geographic locations to infer the epistatic network responsible for the difference between the pre-pandemic virus and the pandemic strain of 2009. These results present a simple and reliable technique to measure epistatic interactions of any sign from sequence data.

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An evolution-based high-fidelity method of epistasis measurement: theory and application to influenza

10.1101/2019.12.11.873307 ◽

2019 ◽

Author(s):

Gabriele Pedruzzi ◽

Igor M. Rouzine

Keyword(s):

Influenza A ◽

Fitness Landscape ◽

Sequence Data ◽

Measurement Theory ◽

Positive Interactions ◽

Stochastic Noise ◽

Reliable Technique ◽

Influenza A H1n1 ◽

Genetic Sequences ◽

Linkage Effects

AbstractLinkage effects in a multi-locus population strongly influence its evolution. The models based on the traveling wave approach enable us to predict the speed of evolution and the statistics of phylogeny. However, predicting the evolution of specific sites and pairs of sites in the multi-locus context remains a mathematical challenge. In particular, the effects of epistasis, the interaction of gene regions contributing to phenotype, is difficult both to predict theoretically and detect experimentally in sequence data. A large number of false interactions arise from stochastic linkage effects and indirect interactions, which mask true interactions. Here we develop a method to filter out false-positive interactions. We start by demonstrating that the averaging of the two-way haplotype frequencies over a multiple independent populations is necessary but not sufficient, because it still leaves high numbers of false interactions. To compensate for this residual stochastic noise, we develop a triple-way haplotype method isolating true interactions. The fidelity of the method is confirmed using simulated genetic sequences evolved with a known epistatic network. The method is then applied to a large database sequences of neurominidase protein of influenza A H1N1 obtained from various geographic locations to infer the epistatic network responsible for the difference between the pre-pandemic virus and the pandemic strain of 2009. These results present a simple and reliable technique to measure site-site interactions from sequence data.Author’s summaryInteraction of genomic sites creating “fitness landscape” is very important for predicting the escape of viruses from drugs and immune response and for passing through fitness valleys. Many efforts have been invested into measuring these interactions from DNA sequence sets. Unfortunately, reproducibility of the results remains low, due partly to a very small fraction of interaction pairs, and partly to stochastic noise intrinsic for evolution masking true interactions. Here we propose a method based on analysis of genetic sequences at three genomic sites to clean stochastic linkage and apply it to influenza virus sequence data.

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Comparison of the Long-Term Immunogenicity of Two Pandemic Influenza A/H1N1 2009 Vaccines, the MF59-Adjuvanted and Unadjuvanted Vaccines, in Adults

Clinical and Vaccine Immunology ◽

10.1128/cvi.00026-12 ◽

2012 ◽

Vol 19 (5) ◽

pp. 638-641 ◽

Cited By ~ 11

Author(s):

Joon Young Song ◽

Hee Jin Cheong ◽

Yu Bin Seo ◽

In Seon Kim ◽

Ji Yun Noh ◽

...

Keyword(s):

Influenza Vaccine ◽

Pandemic Influenza ◽

Influenza A ◽

Geometric Mean ◽

European Medicines Agency ◽

Adjuvanted Vaccine ◽

Conventional Dose ◽

Influenza A H1n1 ◽

The Difference

ABSTRACTSince the first reports of the A/H1N1 virus in April 2009, the pandemic influenza virus spread globally and circulated for a long time. The primary method for the control of influenza is vaccination, but levels of influenza vaccine-induced antibody are known to decline rapidly during a 6-month period. In adults aged 18 to 64 years, we compared the long-term immunogenicity of two of the influenza A/H1N1 2009 monovalent vaccines, 3.75-μg MF59-adjuvanted vaccine and 15-μg unadjuvanted vaccine. The serum hemagglutinin inhibition (HI) titers were determined prevaccination and at 1, 6, and 10 months after vaccination. One hundred six (88.3%) of the 120 subjects were monitored for the entire 10-month period after receiving the influenza A/H1N1 2009 monovalent vaccine. There were 60 patients who received the unadjuvanted vaccine and 46 patients who received the MF59-adjuvanted vaccine. The seroprotection rates, seroconversion rates, and the geometric mean titer (GMT) folds fulfilled the criteria of the European Medicines Agency (EMA) for influenza A/California/7/2009 (H1N1) at 1 month after vaccination irrespective of the vaccine composition. Although the GMTs at 1 month postvaccination were somewhat higher in the unadjuvanted vaccine recipients than in the MF59-adjuvanted vaccine recipients, the difference was not significant (P= 0.29). The seroprotection rates at 6 and 10 months postvaccination were preserved above 70% but only in the MF59-adjuvanted vaccine recipients. In conclusion, low-dose MF59-adjuvanted influenza vaccine, even with 3.75 μg hemagglutinin antigen, might induce excellent long-term immunity that is comparable to the conventional dose of unadjuvanted vaccine among healthy adults aged 18 to 64 years.

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The Attack Rate of H1N1 in Various Berthing Configurations On Board an Aircraft Carrier

Disaster Medicine and Public Health Preparedness ◽

10.1017/dmp.2013.9 ◽

2013 ◽

Vol 7 (2) ◽

pp. 131-135 ◽

Cited By ~ 1

Author(s):

Jared L. Harwood ◽

Joseph T. LaVan ◽

George J. Brand

Keyword(s):

Living Arrangements ◽

Attack Rate ◽

Influenza A ◽

H1n1 Influenza ◽

Occupancy Rate ◽

Group Affiliation ◽

Aircraft Carrier ◽

Living Space ◽

Influenza A H1n1 ◽

The Difference

AbstractObjectiveWe compared attack rates for novel H1N1 influenza A (H1N1) among various groups aboard an aircraft carrier as influenced by characteristics of their living arrangements.MethodsDuring an outbreak of H1N1 on board the USS George Washington (GW), group affiliation (department or squadron membership) data were obtained on all patients who were placed in respiratory isolation based on their diagnosis with presumptive H1N1. Because berthing spaces are assigned by department and various characteristics of each department's berthing spaces are known, analysis of attack rates in comparison to these characteristics was possible. Attack rates were compared with the square feet of living space per sailor, occupancy rate of the berthing areas, and size of the berthing areas. These results were further correlated with the mission of the various departments or squadrons.ResultsThe average attack rate was 3%, with the highest rates occurring in departments or squadrons whose mission required ongoing contact with civilian populations ashore. The attack rate among officers was 2.04 versus 3.19 among enlisted personnel; this difference was not significant (P = .21). The attack rate for women was 1.90 versus 3.09 for men, which was significant (P = .05). Although attack rates varied considerably based on organizational mission, no correlation was found between attack rate and square feet of living space per person or occupancy rate or size of berthing spaces.ConclusionsThe attack rate of the outbreak overall was limited to 3%. Smaller and more crowded berthing configurations did not contribute to higher attack rates, suggesting that transmission occurs most frequently elsewhere while engaged in other activities such as working, eating, or relaxing. Further studies are necessary to filter out potential correlations or variables not identified in this study, such as the difference between the number of men and women isolated. (Disaster Med Public Health Preparedness. 2012;0:1-5)

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Transmission routes of influenza A(H1N1)pdm09: analyses of inflight outbreaks

Epidemiology and Infection ◽

10.1017/s0950268818001772 ◽

2018 ◽

Vol 146 (13) ◽

pp. 1731-1739 ◽

Cited By ~ 3

Author(s):

H. Lei ◽

J. W. Tang ◽

Y. Li

Keyword(s):

Influenza A ◽

Index Case ◽

Meta Analysis ◽

Convincing Evidence ◽

Flight Duration ◽

Influenza A H1n1 ◽

Outbreak Investigations ◽

The Difference ◽

The Relationship ◽

Index Cases

AbstractKnowledge about the infection transmission routes is significant for developing effective intervention strategies. We searched the PubMed databases and identified 10 studies with 14 possible inflight influenza A(H1N1)pdm09 outbreaks. Considering the different mechanisms of the large-droplet and airborne routes, a meta-analysis of the outbreak data was carried out to study the difference in attack rates for passengers within and beyond two rows of the index case(s). We also explored the relationship between the attack rates and the flight duration and/or total infectivity of the index case(s). The risk ratios for passengers seated within and beyond the two rows of the index cases were 1.7 (95% confidence interval (CI) 0.98–2.84) for syndromic secondary cases and 4.3 (95% CI 1.25–14.54) for laboratory-confirmed secondary cases. Furthermore, with an increase of the product of the flight duration and the total infectivity of the index cases, the overall attack rate increased linearly. The study indicates that influenza A(H1N1)pdm09 may mainly be transmitted via the airborne route during air travel. A standardised approach for the reporting of such inflight outbreak investigations would help to provide more convincing evidence for such inflight transmission events.

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A Novel Strategy Facilitates Reference Gene Selection by RT-qPCR Analysis in Kidney Yang Deficiency Syndrome Mice Infected with the Influenza A (H1N1) Virus

BioMed Research International ◽

10.1155/2020/9075165 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Yepei Fu ◽

Jia Yang ◽

Shanshan Fan ◽

Shaozhe Zhao ◽

Syed Muhammad Ali Shah ◽

...

Keyword(s):

Reference Gene ◽

Reference Genes ◽

Influenza A ◽

Gene Selection ◽

Quantitative Polymerase Chain Reaction ◽

Deficiency Syndrome ◽

Pcr Analysis ◽

Influenza A H1n1 ◽

Kidney Yang Deficiency ◽

The Difference

In reverse transcription-quantitative polymerase chain reaction (RT-qPCR) studies, endogenous reference genes are routinely used to normalize the expression of target gene studies. In order to precisely evaluate the relative expression of genes in the cells of mice suffering from Kidney Yang Deficiency Syndrome (KYDS) in response to influenza A virus (IAV) H1N1 using RT-qPCR, it is crucial to identify reliable reference genes. In the present study, 15 candidate reference genes (Actb, β2m, Gapdh, Gusb, Tuba, Grcc10, Eif4h, Rnf187, Nedd8, Ywhae, 18S rRNA, Rpl13, Ubc, Rpl32, and Ppia) were investigated in lung cells from KYDS mice infected with IAV H1N1. NormFinder, BestKeeper, and GeNorm were used to assess the stability of reference genes. The results were authenticated over extended experimental settings by a group of 10 samples. In the present study, we explored a novel method using dual-gene combinations; the difference in gene expression between the model and normal control groups was statistically analyzed by an independent-samples t-test, and the difference in the mean value between the two groups was compared. A P value > 0.05 and the lowest absolute value of the difference indicated the optimal reference two-gene combination. Four additional host innate immune system-related genes (TLR3, TLR4, TLR7, and RIG-I) were analyzed together with the two treatment datasets to confirm the selected reference genes. Our results indicated that none of these 15 candidate reference genes can be used as reference gene individually for relative quantitative fluorescence PCR analysis; however, the combination of Grcc10 and Ppia, based on the process of calculating the higher P value and lower difference values between groups, was the best choice as a reference gene for the lung tissue samples in KYDS mice infected with IAV. This technique may be applied to promote the selection process of the optimal reference gene in other experiments.

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Mouse Dendritic Cell (DC) Influenza Virus Infectivity Is Much Lower than That for Human DCs and Is Hemagglutinin Subtype Dependent

Journal of Virology ◽

10.1128/jvi.02980-12 ◽

2012 ◽

Vol 87 (3) ◽

pp. 1916-1918 ◽

Cited By ~ 13

Author(s):

Boris M. Hartmann ◽

Wenjing Li ◽

Jingjing Jia ◽

Sonali Patil ◽

Nada Marjanovic ◽

...

Keyword(s):

Influenza A ◽

H1n1 Virus ◽

Virus Infectivity ◽

Recombinant Viruses ◽

Influenza A H1n1 ◽

The Difference ◽

Viruslike Particles ◽

Mouse Dendritic Cell ◽

H1n1 Virus Infection

ABSTRACTWe show that influenza A H1N1 virus infection leads to very low infectivity in mouse dendritic cells (DCs)in vitrocompared with that in human DCs. This holds when H3 or H5 replaces H1 in recombinant viruses. Viruslike particles confirm the difference between mouse and human, suggesting that reduced virus entry contributes to lower mouse DC infectivity. Low infectivity of mouse DCs should be considered when they are used to study responses of DCs that are actually infected.

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Characterizing the Countrywide Epidemic Spread of Influenza A(H1N1)pdm09 Virus in Kenya between 2009 and 2018

Viruses ◽

10.3390/v13101956 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1956

Author(s):

D. Collins Owuor ◽

Zaydah R. de Laurent ◽

Gilbert K. Kikwai ◽

Lillian M. Mayieka ◽

Melvin Ochieng ◽

...

Keyword(s):

Genetic Diversity ◽

Influenza A ◽

Sequence Data ◽

Influenza Viruses ◽

Seasonal Fluctuations ◽

Middle Income ◽

Full Diversity ◽

Virus Diversity ◽

Pdm09 Virus ◽

Influenza A H1n1

The spatiotemporal patterns of spread of influenza A(H1N1)pdm09 viruses on a countrywide scale are unclear in many tropical/subtropical regions mainly because spatiotemporally representative sequence data are lacking. We isolated, sequenced, and analyzed 383 A(H1N1)pdm09 viral genomes from hospitalized patients between 2009 and 2018 from seven locations across Kenya. Using these genomes and contemporaneously sampled global sequences, we characterized the spread of the virus in Kenya over several seasons using phylodynamic methods. The transmission dynamics of A(H1N1)pdm09 virus in Kenya were characterized by (i) multiple virus introductions into Kenya over the study period, although only a few of those introductions instigated local seasonal epidemics that then established local transmission clusters, (ii) persistence of transmission clusters over several epidemic seasons across the country, (iii) seasonal fluctuations in effective reproduction number (Re) associated with lower number of infections and seasonal fluctuations in relative genetic diversity after an initial rapid increase during the early pandemic phase, which broadly corresponded to epidemic peaks in the northern and southern hemispheres, (iv) high virus genetic diversity with greater frequency of seasonal fluctuations in 2009–2011 and 2018 and low virus genetic diversity with relatively weaker seasonal fluctuations in 2012–2017, and (v) virus spread across Kenya. Considerable influenza virus diversity circulated within Kenya, including persistent viral lineages that were unique to the country, which may have been capable of dissemination to other continents through a globally migrating virus population. Further knowledge of the viral lineages that circulate within understudied low-to-middle-income tropical and subtropical regions is required to understand the full diversity and global ecology of influenza viruses in humans and to inform vaccination strategies within these regions.

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Harnessing DNA Synthesis to Develop Rapid Responses to Emerging and Pandemic Pathogens

Journal of Pathogens ◽

10.4061/2011/765763 ◽

2011 ◽

Vol 2011 ◽

pp. 1-7

Author(s):

Lisa M. Runco ◽

J. Robert Coleman

Keyword(s):

Dna Synthesis ◽

Influenza A ◽

Sequence Data ◽

H1n1 Pandemic ◽

Emerging Pathogens ◽

Economic Stability ◽

Rapid Responses ◽

Influenza A H1n1 ◽

Biomedical Community

Given the interconnected nature of our world today, emerging pathogens and pandemic outbreaks are an ever-growing threat to the health and economic stability of the global community. This is evident by the recent 2009 Influenza A (H1N1) pandemic, the SARS outbreak, as well as the ever-present threat of global bioterrorism. Fortunately, the biomedical community has been able to rapidly generate sequence data so these pathogens can be readily identified. To date, however, the utilization of this sequence data to rapidly produce relevant experimental results or actionable treatments is lagging in spite of obtained sequence data. Thus, a pathogenic threat that has emerged and/or developed into a pandemic can be rapidly identified; however, translating this identification into a targeted therapeutic or treatment that is rapidly available has not yet materialized. This commentary suggests that the growing technology of DNA synthesis should be fully implemented as a means to rapidly generatein vivodata and possibly actionable therapeutics soon after sequence data becomes available.

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Effect of Changes in the Age Structure of the Population in the Incidence of Influenza and ARI in the Cities of Russia from 1986 to 2014

Epidemiology and Vaccinal Prevention ◽

10.31631/2073-3046-2015-14-6-6-15 ◽

2015 ◽

Vol 14 (6) ◽

pp. 6-15

Author(s):

T. I. Sysoeva ◽

L. S. Karpova

Keyword(s):

Age Structure ◽

Influenza A ◽

Age Groups ◽

Average Correlation ◽

Total Incidence ◽

Younger Age ◽

Influenza A H1n1 ◽

The Difference ◽

The Impact ◽

Observation Period

In order to study the dynamics of the incidence of influenza and ARI in the cities of Russia and the impact of the demographic composition of its population we evaluated changes in the age structure of the population from 1986 to 2014. Considerable changes in the 28 years dynamics of the total incidence of influenza and ARI revealed. The highest incidence rate from 1969 to 1990 gave way to decrease in the incidence from 1991 to 2008 in all cities, especially in megacities, and to increase during the influenza A(H1N1)pdm09 circulation. Reduction of the differences in the incidence of influenza and ARI in cities with different population is noted. From 1969 to 2014 there have been significant changes in the dynamics of influenza and ARI incidence: reduction in the incidence from 1991 in all the cities, especially in megacities, increasing of incidence during the influenza A(H1N1)pdm09 circulation years from 2009 to 2014, and reducing the difference in the incidence of influenza and ARI in cities with varying populations. In most cities, the incidence remained high throughout the observation period. In 2009 - 2014 the incidence has become higher in the Barnaul, Irkutsk, Yakutsk, and Yuzhno-Sakhalinsk, and lower in the Krasnodar and Ulan-Ude compared with the periods from 1986 to 2008. The results from correlation analysis reveal that incidence of influenza and ARI is significantly positively correlated with the age and number of children's groups, more pronounced in the younger age groups, at 95% confidence level. Children 0 - 2 years revealed significant strong correlation in 27 of the 34 cities, the average correlation coefficient, R = 0.75, children 3 - 6 years - a strong (in 16 cities) and the average (in 16 cities), R = 0.63, children 7 - 14 years - a strong (in 9 cities) and average (in 15 cities), R = 0.53, in adults found an association of moderate strength only in 8 cities R = 0.48.

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Characterizing the countrywide epidemic spread of influenza A(H1N1)pdm09 virus in Kenya between 2009 and 2018

10.1101/2021.03.30.21254587 ◽

2021 ◽

Author(s):

D. Collins Owuor ◽

Zaydah R. de Laurent ◽

Gilbert K. Kikwai ◽

Lillian M. Mayieka ◽

Melvin Ochieng ◽

...

Keyword(s):

Genetic Diversity ◽

Influenza A ◽

Sequence Data ◽

Influenza Viruses ◽

Seasonal Fluctuations ◽

Middle Income ◽

Virus Diversity ◽

Pdm09 Virus ◽

Geographical Regions ◽

Influenza A H1n1

ABSTRACTBackgroundThe spatiotemporal patterns of spread of influenza A(H1N1)pdm09 viruses on a countrywide scale are unclear in many tropical/subtropical regions mainly because spatiotemporally representative sequence data is lacking.MethodsWe isolated, sequenced, and analyzed 383 influenza A(H1N1)pdm09 viral genomes isolated from hospitalized patients between 2009 and 2018 from seven locations across Kenya. Using these genomes and contemporaneously sampled global sequences, we characterized the spread of the virus in Kenya over several seasons using phylodynamic methods.ResultsThe transmission dynamics of influenza A(H1N1)pdm09 virus in Kenya was characterized by: (i) multiple virus introductions into Kenya over the study period, although these were remarkably few, with only a few of those introductions instigating seasonal epidemics that then established local transmission clusters; (ii) persistence of transmission clusters over several epidemic seasons across the country; (iii) seasonal fluctuations in effective reproduction number (Re) associated with lower number of infections and seasonal fluctuations in relative genetic diversity after an initial rapid increase during the early pandemic phase, which broadly corresponded to epidemic peaks in the northern and southern hemispheres; (iv) high virus genetic diversity with greater frequency of seasonal fluctuations in 2009-11 and 2018 and low virus genetic diversity with relatively weaker seasonal fluctuations in 2012-17; and (v) virus migration from multiple geographical regions to multiple geographical destinations in Kenya.ConclusionConsiderable influenza virus diversity circulates within Africa, as demonstrated in this report, including virus lineages that are unique to the region, which may be capable of dissemination to other continents through a globally migrating virus population. Further knowledge of the viral lineages that circulate within understudied low-to-middle income tropical and subtropical regions is required to understand the full diversity and global ecology of influenza viruses in humans and to inform vaccination strategies within these regions.

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