Journal: bioRxiv

Article Title: Influenza A viruses use multivalent sialic acid clusters for cell binding and receptor activation

doi: 10.1101/264713

Figure Lengend Snippet: ( A ) Influenza virus is an enveloped particle that encapsulates the segmented (-)vRNA genome built of 8 viral ribonucleoprotein particles (vRNPs). The viral membrane harbors the two glycoproteins hemagglutinin (HA) and neuraminidase (NA). HA is responsible for binding sialic acid (SA) containing attachment factors on the host cell plasma membrane. Upon cell-binding, the virus needs to activate functional receptors to trigger endocytosis. ( B ) Confocal imaging of live A549 cells labelled with SNA and Hoechst (DNA) feature a nonuniform SNA distribution across the plasma membrane. Large finger-like protrusions can be observed on the apical plasma membrane. ( C ) Confocal and STED live-cell imaging of A549 cells labelled with SNA confirms the existence of finger-like protrusions as well as a population of smaller nanodomains with diameter of ∼100 nm ( C , right, inset). ( D ) Further, we utilized STORM imaging of A549 cells labelled with SNA. Reconstructed STORM images confirm two major structural features (1) finger-like protrusions as well as (2) small nanodomains. Cell treatment with neuraminidase (NA, 0.01 U/ml for 2h) led to a strong reduction of the localization density due to the cleavage and hence decrease local concentration of SA ( D , right, inset).

Article Snippet: A549 cells (ATCC CCL-185) were kindly provided by Dr. Thorsten Wolff (Robert-Koch Institute Berlin, Germany).

Techniques: Virus, Membrane, Binding Assay, Clinical Proteomics, Functional Assay, Imaging, Live Cell Imaging, Concentration Assay

Journal: bioRxiv

Article Title: Influenza A viruses use multivalent sialic acid clusters for cell binding and receptor activation

doi: 10.1101/264713

Figure Lengend Snippet: ( A ) Spatial distribution of STORM localizations from SNA-A647 on A549 cells showing the coexistence of two structural features, (1) large microvilli as well as (2) small nanodomains. The inset in A shows a rendered reconstruction (10 nm/pxl) of the localization map in A . ( B ) Density distribution of localizations shown in A within a search radius of 50 nm. Color scale according to number of neighbor localizations. ( C ) Final cluster identification with identified clusters in random color code. ( D ) Distribution of cluster area. The cluster identification allows quantification of the cluster area. After all identified clusters were filtered according to their size to selectively analyze non-microvilli structures, we found clusters with an area between 0.5 - 4 * 10 4 nm 2 . Distribution of the number of molecules per cluster as estimated according to the number of localizations ( D , inset).

Article Snippet: A549 cells (ATCC CCL-185) were kindly provided by Dr. Thorsten Wolff (Robert-Koch Institute Berlin, Germany).

Techniques:

Journal: bioRxiv

Article Title: Influenza A viruses use multivalent sialic acid clusters for cell binding and receptor activation

doi: 10.1101/264713

Figure Lengend Snippet: Based on our quantitative analysis of the AF distribution on A549 cells, we hypothesize a motion behavior that is driven by the local AF concentration. We simulate this behavior initially as a 2D random walk with free diffusion coefficient D free ( A ). ( B ) Next, we simulate AF clusters (red circles, r = 100 nm), which would due to the increased SA concentration lead to a temporal confinement (D conf < D free ). To identify confined regions within the simulated virus trajectories, we establish a confinement index I conf . Accordingly, a free diffusing particle shows only fluctuation in of I conf ( D ), while the addition of temporal confinement leads to a clear increase that overlaps with stationary phases of the particle as visible in the XY displacement plot ( E ). We used the confinement probability to analyze experimental virus trajectories in particular the mixed type of trajectories ( C ) (see also Fig. S5) ( C ). I conf shows a clear signature of temporal confinement ( F ) similar to the model prediction ( E ). As a further challenge for our model, we performed a subtrajectory analysis, thereby extracting the dwell time, Dconf as well as the area of the respective temporal confinement in our virus trajectories. ( G ) shows an overlay of the perimeters of the extracted confined regions as well as the average radius (R). From our simulated data, correlation of D conf with the dwell time shows that a local increase in AF concentration (i.e. decreased diffusion) due to the encounter of an SA nanodomain leads to an increased local dwell time ( H , red markers). We observed a similar behavior, when we tested the confinement dwell time in experimental virus trajectories ( H , black markers).

Article Snippet: A549 cells (ATCC CCL-185) were kindly provided by Dr. Thorsten Wolff (Robert-Koch Institute Berlin, Germany).

Techniques: Concentration Assay, Diffusion-based Assay, Virus

Journal: bioRxiv

Article Title: Influenza A viruses use multivalent sialic acid clusters for cell binding and receptor activation

doi: 10.1101/264713

Figure Lengend Snippet: ( A ) A549 cells were labelled with antibodies against EGFR. STORM imaging revealed a clustered organization of EGFR on the apical plasma membrane. The clusters have an average diameter of 60 nm and contain about 5 - 10 molecules ( B ). Scale bar 1 μm. Inset: 100 nm. ( C ) Two-color STORM imaging of A549 cells labelled with SNA and anti-EGFR antibodies. The two panels on the right show larger magnification of the boxed areas in the left panel. Scale bars: 500 nm (left panel), 200 nm (right panel). The degree of colocalization was quantified using coordinate-based colocalization, where each localization is associated with a colocalization value C A . ( D ) Box plots of C A distribution of SNA localizations when colocalized with (1) SNA, (2) a random distribution of localizations at equal density as EGFR and (3) EGFR. After stimulating the cells, we found that phosphorylated EGFR (Y1068) is also localized in nanodomains, suggesting activation of pre-formed cluster. Although a small population of clusters seems to be phosphorylated without stimulus, we observed an increase in the activated cluster population after stimulation with IAV or EGF ( E , lower panel). To test for a potential redistribution of EGFR, we looked at the entire population after stimulation. While after EGF stimulation, we could observe a reduction of the clustered protein fraction as well as the cluster density per area, we could not detect such a protein redistribution after IAV stimulation ( F ).

Article Snippet: A549 cells (ATCC CCL-185) were kindly provided by Dr. Thorsten Wolff (Robert-Koch Institute Berlin, Germany).

Techniques: Imaging, Clinical Proteomics, Membrane, Activation Assay

Journal: bioRxiv

Article Title: Influenza A viruses use multivalent sialic acid clusters for cell binding and receptor activation

doi: 10.1101/264713

Figure Lengend Snippet: EGFR coupled to the photo-convertible protein mEos3 was expressed in A549 cells. Subsequent PALM imaging allows to study EGFR distribution in live cells at the single protein level. In the absence of any stimulus, we could detect nanodomains of EGFR within the apical and also the basolateral plasma membrane ( A ). Scale bar: left panel, 1 μm. The image in A shows a maximum projected map of single molecule localizations recorded over a period of 10 min. B shows two cluster examples as a cumulative density distribution (upper panel) as well as XY scatter with the colorscale according to time at which the localization was detected (lower panel). While the projection of all localization allows to identify protein clusters, we can use the time information to further estimate the cluster lifetime. As shown in C , cumulative counting of individual localizations within a clustered region gives direct information of the minimum cluster lifetime. D shows the corresponding lifetime distribution of EGFR clusters recorded at the apical as well as the basolateral membrane in the absence of any stimulus.

Article Snippet: A549 cells (ATCC CCL-185) were kindly provided by Dr. Thorsten Wolff (Robert-Koch Institute Berlin, Germany).

Techniques: Imaging, Clinical Proteomics, Membrane

Journal: bioRxiv

Article Title: Influenza A viruses use multivalent sialic acid clusters for cell binding and receptor activation

doi: 10.1101/264713

Figure Lengend Snippet: Using quantitative STORM imaging, we could show that SA-conjugated IAV AF as well as one functional receptor, EGFR, form nanodomains in the plasma membrane of A549 cells. While dense AF nanodomains constitute an attractive multivalent binding platform, their diversity in local AF concentration suggests a variety of different residence times for which IAV would stay bound within these domains. Using single-virus tracking, we observed a mixed diffusive - confined motion, that could be simulated using our quantitative SA cluster information. These data suggest a receptor concentration-driven lateral search mechanism between SA enriched nanodomains. Eventually, since AF domains partly overlap with EGFR, IAV encounters a functional receptor that can be activated to signal cell entry. Our data further suggest that a stable pre-formed EGFR cluster population is activated during IAV stimulation, thereby possibly facilitating efficient signal transduction. EGFR clusters are stabilized by lipid rafts as well as cortical actin.

Article Snippet: A549 cells (ATCC CCL-185) were kindly provided by Dr. Thorsten Wolff (Robert-Koch Institute Berlin, Germany).

Techniques: Imaging, Functional Assay, Clinical Proteomics, Membrane, Binding Assay, Concentration Assay, Virus, Transduction

Journal: bioRxiv

Article Title: Epromoters bind key stress-related transcription factors to regulate clusters of stress response genes

doi: 10.1101/2024.11.26.625372

Figure Lengend Snippet: (A) Schematic representation of the pipeline steps to identify Epromoter-regulated gene clusters. (B) Schematic overview of the two clustering methods used in the pipeline. (Left) Clustering of stress-induced genes based on the proximity of their TSS within a 100 kb distance. (Right) Clustering of stress-induced genes based on their localization within the same TAD. (C) Schematic representation of the “Vihervaara” dataset to induce the HS response. (D) (left) Bubble plot showing the number of all the clusters identified by their number of promoters (x-axis) compared to their number of promoters recruiting HSF1 (y-axis) determined by the pipeline. (right) Bubble plot showing the number of all the clusters identified by their number of promoters (x-axis) compared to their number of promoters recruiting HSF2 (y-axis) determined by the pipeline. (E) Venn diagram displaying the overlap of Epromoter-regulated clusters identified after clustering either by the distance between the TSS or their localization within the same TAD in the HS response. (F) Example of the PGGHG Epromoter-regulated cluster identified by the pipeline with the two clustering methods in the HS stress response. The genomic tracks show the PRO-seq signal (red) and HSF1 and HSF2 ChIP-seq signal (blue) before or after HS from the “Vihervaara” dataset. The topological associating domains (TAD) from K562 is displayed on the top. The fold-change of induction is indicated below the name and orientation of the genes (Epromoter: green, co-induced genes: yellow). (G) Luciferase assays to quantify the enhancer activity of predicted Epromoter (on the right) and induced promoters clustered with Epromoters (on the left) before (blue) and after (red) HS in the K562 cells. The results were normalized on the pGL4-SV40 promoter plasmid. P values were calculated by a paired one-sided Student’s t-test. (insert) Luciferase assay-induced enhancer activity represented by the fold change before/after HS for the predicted Epromoter and the induced promoters. P values were calculated by a two-sided Wilcoxon’s test, *** P < 0.001, ** P < 0.01, * P < 0.1. (H) (top panel) Representation of the classification of the HS-induced genes in 4 categories. (bottom panel) Percent stacked barplot of the numbers of motifs (HSE) per promoter in each category. The number of motifs is divided into 0 motif (blue), 1 motif (cyan), 2 to 3 motifs (yellow), and more than 3 motifs (red).

Article Snippet: Cell line K562 (CCL-243), a chronic myelogenous leukemia cell line, was obtained from the ATCC (American Type Culture Collection) and maintained in RPMI 1640 media (Thermo Fischer Scientific) supplemented with 10% FBS (Thermo Fischer Scientific) at 37°C and 5% CO2.

Techniques: ChIP-sequencing, Luciferase, Activity Assay, Plasmid Preparation

Journal: bioRxiv

Article Title: Epromoters bind key stress-related transcription factors to regulate clusters of stress response genes

doi: 10.1101/2024.11.26.625372

Figure Lengend Snippet: (A) The NUCB1 Epromoter-regulated cluster. (top) Hi-C triangular matrix (resolution 5kb) of the locus from K562 cells. The genomic tracks show the PRO-seq signal (in red) and HSF1 and HSF2 ChIP-seq signal (in blue) before or after HS from the “Vihervaara” dataset. The fold-change of induction is indicated below the name and orientation of the genes (Epromoter: green, co-induced genes: yellow). (B) Luciferase assays to quantify the promoter activity of the induced DHDH promoter with or without the NUCB1 Epromoter acting as an enhancer before and after HS in K562 cells. P values were calculated by a paired one-sided Student’s t-test, *** P < 0.001, ** P < 0.01, * P < 0.1. (C) Schematic of the CRISPR-Cas9 genome deletion and re-insertion of the promoter region of the NUCB1 Epromoter in K562 cells. (d) qPCR analysis of TULP2 , NUCB1 , and DHDH expression in wild type and 4 ΔNUCB1 mutants in K562 cells before and after HS. Values represent the relative expression of the samples normalized to the housekeeping gene GAPDH and compared to the unstressed wild-type cells. P values were calculated by a two-sided Student’s t-test, *** P < 0.001, ** P < 0.01, * P < 0.1. (E) qPCR analysis of the DHDH expression in 2 ΔNUCB1 mutants, 2 heterozygote ΔNUCB1-inserted mutants (green, blue), and 2 homozygote ΔNUCB1-inserted mutants in K562 cells before and after HS. Values represent the relative expression of the samples normalized to the housekeeping gene GAPDH , then compared before and after HS. P values were calculated by a two-sided Student’s t-test, *** P < 0.001, ** P < 0.01, * P < 0.1. (F) qPCR analysis of the promoter activity in 2 ΔNUCB1 mutants, 2 heterozygote ΔNUCB1-inserted mutants, and 2 homozygote ΔNUCB1-inserted mutants in K562 cells before and after HS. Values represent the relative expression of the samples normalized to the housekeeping gene GAPDH and compared to the mean of the ΔNUCB1 clones. P values were calculated by a two-sided Student’s t-test, *** P < 0.001, ** P < 0.01, * P < 0.1.

Article Snippet: Cell line K562 (CCL-243), a chronic myelogenous leukemia cell line, was obtained from the ATCC (American Type Culture Collection) and maintained in RPMI 1640 media (Thermo Fischer Scientific) supplemented with 10% FBS (Thermo Fischer Scientific) at 37°C and 5% CO2.

Techniques: Hi-C, ChIP-sequencing, Luciferase, Activity Assay, CRISPR, Expressing, Clone Assay