scholarly journals Influenza A virus hemagglutinin prevents extensive membrane damage upon dehydration

2021 ◽  
Author(s):  
Maiara A. Iriarte-Alonso ◽  
Salvatore Chiantia ◽  
Alexander M. Bittner
Keyword(s):  
Relative Humidity ◽  
Influenza A ◽  
Molecular Mechanisms ◽  
Membrane Damage ◽  
Correlation Spectroscopy ◽  
Viral Envelope ◽  
Image Correlation ◽  
Membrane Properties ◽  
Virus Infectivity ◽  
Influenza A H1n1

While the molecular mechanisms of virus infectivity are rather well known, the detailed consequences of environmental factors on virus biophysical properties are poorly understood. 20 Seasonal influenza outbreaks are usually connected to the low winter temperature, but also to the low relative air humidity. Indeed, transmission rates increase in cold regions during winter. While low temperature must slow degradation processes, the role of low humidity is not clear. We studied the effect of relative humidity on a model of influenza A H1N1 virus envelope, a supported lipid bilayer containing the surface glycoprotein hemagglutinin (HA), which is 25 present in the viral envelope in very high density. For complete cycles of hydration, dehydration and rehydration, we evaluate the membrane properties in terms of structure and dynamics, which we assess by combining confocal fluorescence microscopy, raster image correlation spectroscopy, line-scan fluorescence correlation spectroscopy and atomic force microscopy. Our findings indicate that the presence of HA prevents macroscopic membrane 30 damage after dehydration. Without HA, fast membrane disruption is followed by irreversible loss of lipid and protein mobility. Although our model is principally limited by the membrane composition, the macroscopic effects of HA under dehydration stress reveal new insights on the stability of the virus at low relative humidity.

scholarly journals Multi-color fluorescence fluctuation spectroscopy in living cells via spectral detection

2020 ◽  
Author(s):  
Valentin Dunsing ◽  
Annett Petrich ◽  
Salvatore Chiantia
Keyword(s):  
Correlation Analysis ◽  
Influenza A ◽  
Cross Correlation ◽  
Matrix Protein ◽  
Living Cells ◽  
Correlation Spectroscopy ◽  
Image Correlation ◽  
Fluorescence Fluctuation Spectroscopy ◽  
Diffusion Dynamics ◽  
Cross Correlation Analysis

AbstractFluorescence fluctuation spectroscopy provides a powerful toolbox to quantify transport dynamics and interactions between biomolecules in living cells. For example, cross-correlation analysis of spectrally separated fluctuations allows the investigation of inter-molecular interactions. This analysis is conventionally limited to two fluorophore species that are excited with a single or two different laser lines and detected in two non-overlapping spectral channels. However, signaling pathways in biological systems often involve interactions between multiple biomolecules, e.g. formation of ternary or quaternary protein complexes. Here, we present a methodology to investigate such interactions at the plasma membrane (PM) of cells, as encountered for example in viral assembly or receptor-ligand interactions. To this aim, we introduce scanning fluorescence spectral correlation spectroscopy (SFSCS), a combination of scanning fluorescence correlation spectroscopy with spectrally resolved detection and decomposition. We first demonstrate that SFSCS allows cross-talk-free cross-correlation analysis of PM-associated proteins labeled with strongly overlapping fluorescent proteins (FPs), such as mEGFP and mEYFP, excited with a single excitation line. We then verify the applicability of SFSCS for quantifying diffusion dynamics and protein oligomerization (based on molecular brightness analysis) of two protein species tagged with spectrally overlapping FPs. Adding a second laser line, we demonstrate the possibility of three- and four-species (cross-) correlation analysis using mApple and mCherry2, as examples of strongly overlapping FP tags in the red spectral region. Next, we apply this scheme to investigate the interactions of influenza A virus (IAV) matrix protein 2 (M2) with two cellular host factors simultaneously. Using the same set of fluorophores, we furthermore extend the recently presented raster spectral image correlation spectroscopy (RSICS) approach to four species analysis, successfully demonstrating multiplexed RSICS measurements of protein interactions in the cell cytoplasm. Finally, we apply RSICS to investigate the assembly of the ternary IAV polymerase complex and report a 2:2:2 stoichiometry of these protein assemblies in the nucleus of living cells.

scholarly journals Escherichia coli response to subinhibitory concentration of Colistin: Insights from study of membrane dynamics and morphology.

2022 ◽  
Author(s):  
Ilanila Ilangumaran Ponmalar ◽  
Jitendriya Swain ◽  
Jaydeep Kumar Basu
Keyword(s):  
Bacterial Infections ◽  
Molecular Mechanisms ◽  
Lipid Membrane ◽  
Membrane Dynamics ◽  
Correlation Spectroscopy ◽  
Membrane Properties ◽  
Bacterial Response ◽  
Lipid Dynamics ◽  
The Impact ◽  
Altered Lipid

Prevalence of wide spread bacterial infections bring forth a critical need in understanding the molecular mechanisms of the antibiotics as well as the bacterial response to those antibiotics. Improper usage of antibiotics, which can be in sub-lethal concentrations is one among the multiple reasons for acquiring antibiotic resistance which makes it vital to understand the bacterial response towards sub-lethal concentrations of antibiotics. In this work, we have used colistin, a well-known membrane active antibiotic used to treat severe bacterial infections and explored the impact of its subminimum inhibitory concentration (MIC) on the lipid membrane dynamics and morphological changes of E. coli. Upon investigation of live cell membrane properties such as lipid dynamics using fluorescence correlation spectroscopy, we observed that colistin disrupts the lipid membrane at sub-MIC by altering the lipid diffusivity. Interestingly, filamentationlike cell elongation was observed upon colistin treatment which led to further exploration of surface morphology with the help of atomic force spectroscopy. The changes in the surface roughness upon colistin treatment provides additional insight on the colistin-membrane interaction corroborating with the altered lipid diffusion. Although altered lipid dynamics could be attributed to an outcome of lipid rearrangement due to direct disruption by antibiotic molecules on the membrane or an indirect consequence of disruptions in lipid biosynthetic pathways, we were able to ascertain that altered bacterial membrane dynamics is due to direct disruptions. Our results provide a broad overview on the consequence of the cyclic polypeptide, colistin on membrane specific lipid dynamics and morphology of a live Gram-negative bacterial cell.

scholarly journals Identification of combinatorial and singular genomic signatures of host adaptation in influenza A H1N1 and H3N2 subtypes

2016 ◽  
Author(s):  
Zeeshan Khaliq ◽  
Mikael Leijon ◽  
Sándor Belák ◽  
Jan Komorowski
Keyword(s):  
Influenza A ◽  
Molecular Mechanisms ◽  
Host Adaptation ◽  
H1n1 Subtype ◽  
Species Barrier ◽  
New Host ◽  
Rule Based ◽  
H3n2 Subtype ◽  
Genomic Signatures ◽  
Influenza A H1n1

AbstractBackgroundThe underlying strategies used by influenza A viruses (IAVs) to adapt to new hosts while crossing the species barrier are complex and yet to be understood completely. Several studies have been published identifying singular genomic signatures that indicate such a host switch. The complexity of the problem suggested that in addition to the singular signatures, there might be a combinatorial use of such genomic features, in nature, defining adaptation to hosts..ResultsWe used computational rule-based modeling to identify combinatorial sets of interacting amino acid (aa) residues in 12 proteins of IAVs of H1N1 and H3N2 subtypes. We built highly accurate rule-based models for each protein that could differentiate between viral aa sequences coming from avian and human hosts,. We found 68 combinations of aa residues associated to host adaptation (HAd) on HA, M1, M2, NP, NS1, NEP, PA, PA-X, PB1 and PB2 proteins of the H1N1 subtype and 24 on M1, M2, NEP, PB1 and PB2 proteins of the H3N2 subtypes. In addition to these combinations, we found 132 novel singular aa signatures distributed among all proteins, including the newly discovered PA-X protein, of both subtypes. We showed that HA, NA, NP, NS1, NEP, PA-X and PA proteins of the H1N1 subtype carry H1N1-specific and HA, NA, PA-X, PA, PB1-F2 and PB1 of the H3N2 subtype carry H3N2-specific HAd signatures. M1, M2, PB1-F2, PB1 and PB2 of H1N1 subtype, in addition to H1N1 signatures, also carry H3N2 signatures. Similarly M1, M2, NP, NS1, NEP and PB2 of H3N2 subtype were shown to carry both H3N2 and H1N1 HAd signatures.ConclusionsTo sum it up, we computationally constructed simple IF-THEN rule-based models that could distinguish between aa sequences of virus particles originating from avian and human hosts. From the rules we identified combinations of aa residues as signatures facilitating the adaptation to specific hosts. The identification of combinatorial aa signatures suggests that the process of adaptation of IAVs to a new host is more complex than previously suggested. The present study provides a basis for further detailed studies with the aim to elucidate the molecular mechanisms providing the foundation for the adaptation process.

scholarly journals Influenza A(H1N1)pdm09 outbreak detected in inter-seasonal months during the surveillance of influenza-like illness in Pune, India, 2012–2015

2017 ◽  
Vol 145 (9) ◽  
pp. 1898-1909 ◽  
Author(s):  
Y. K. GURAV ◽  
M. S. CHADHA ◽  
B. V. TANDALE ◽  
V. A. POTDAR ◽  
S. D. PAWAR ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Influenza A ◽  
Reproduction Number ◽  
Nasal Discharge ◽  
Age Group ◽  
Community Based ◽  
Influenza Like Illness ◽  
Seasonal Factors ◽  
Influenza A H1n1 ◽  
Influenza Activity

SUMMARYAn outbreak of influenza A(H1N1)pdm09 was detected during the ongoing community-based surveillance of influenza-like illness (ILI). Among reported 119 influenza A(H1N1)pdm09 cases (59 cases in the year 2012 and 60 cases in 2015) in summer months, common clinical features were fever (100%), cough (90·7%), sore throat (85·7%), nasal discharge (48·7%), headache (55·5%), fatigue (18·5%), breathlessness (3·4%), and ear discharge (1·7%). Rise in ILI cases were negatively correlated with the seasonal factors such as relative humidity (Karl Pearson's correlation coefficient, i.e. r = −0·71 in the year 2012 and r = −0·44 in the year 2015), while rise in ILI cases were positively correlated with the temperature difference (r = 0·44 in the year 2012 and r = 0·77 in the year 2015). The effective reproduction number R, was estimated to be 1·30 in 2012 and 1·64 in 2015. The study highlights the rise in unusual influenza activity in summer month with high attack rate of ILI among children aged ⩽9 years. Children in this age group may need special attention for influenza vaccination. Influenza A(H1N1)pdm09 outbreak was confirmed in inter-seasonal months during the surveillance of ILI in Pune, India, 2012–2015.

scholarly journals Influenza A M2 recruits M1 to the plasma membrane: a fluorescence fluctuation microscopy study

2021 ◽  
Author(s):  
Annett Petrich ◽  
Valentin Dunsing ◽  
Sara Bobone ◽  
Salvatore Chiantia
Keyword(s):  
Plasma Membrane ◽  
Influenza A ◽  
Cross Correlation ◽  
Matrix Protein ◽  
Viral Proteins ◽  
Correlation Spectroscopy ◽  
Viral Envelope ◽  
Respiratory Pathogen ◽  
Oligomeric State ◽  
Fluctuation Microscopy

Influenza A virus (IAV) is a respiratory pathogen that causes seasonal epidemics and occasional pandemics of severe illnesses with significant mortality. One of the most abundant proteins in IAV particles is the matrix protein 1 (M1), which is essential for the structural stability of the virus. M1 organizes virion assembly and budding at the plasma membrane (PM), where it can interact with other viral components and cellular membrane factors (i.e. lipids and host proteins). Of interest, the recruitment of M1 to the PM as well as its interaction with the other viral envelope proteins (hemagglutinin (HA), neuraminidase, matrix protein 2 (M2)) is controversially discussed in previous studies. Therefore, we used fluorescence fluctuation microscopy techniques (i.e. (cross-correlation) number and brightness, and scanning fluorescence cross-correlation spectroscopy) to quantify the oligomeric state of M1 and its interaction with other viral proteins in co-transfected as well as infected cells. Our results indicate that M1 is recruited to the PM by M2, as a consequence of the strong interaction between the two proteins. In contrast, only a weak interaction between M1 and HA was observed. M1-HA interaction occurred only in the case that M1 was already bound to the PM. We therefore conclude that M2 initiates the assembly of IAV by recruiting M1 to the PM, possibly allowing its further interaction with other viral proteins.

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

2012 ◽  
Vol 87 (3) ◽  
pp. 1916-1918 ◽  
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.

scholarly journals Multi-color fluorescence fluctuation spectroscopy in living cells via spectral detection

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Valentin Dunsing ◽  
Annett Petrich ◽  
Salvatore Chiantia
Keyword(s):  
Influenza A ◽  
Cross Correlation ◽  
Matrix Protein ◽  
Living Cells ◽  
Correlation Spectroscopy ◽  
Image Correlation ◽  
Protein Species ◽  
Fluorescence Fluctuation Spectroscopy ◽  
Spectral Correlation ◽  
Cross Correlation Analysis

Signaling pathways in biological systems rely on specific interactions between multiple biomolecules. Fluorescence fluctuation spectroscopy provides a powerful toolbox to quantify such interactions directly in living cells. Cross-correlation analysis of spectrally separated fluctuations provides information about inter-molecular interactions but is usually limited to two fluorophore species. Here, we present scanning fluorescence spectral correlation spectroscopy (SFSCS), a versatile approach that can be implemented on commercial confocal microscopes, allowing the investigation of interactions between multiple protein species at the plasma membrane. We demonstrate that SFSCS enables cross-talk-free cross-correlation, diffusion and oligomerization analysis of up to four protein species labeled with strongly overlapping fluorophores. As an example, we investigate the interactions of influenza A virus (IAV) matrix protein 2 with two cellular host factors simultaneously. We furthermore apply raster spectral image correlation spectroscopy for the simultaneous analysis of up to four species and determine the stoichiometry of ternary IAV polymerase complexes in the cell nucleus.

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