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    ATCC influenzae isolates
    (A) Phylogenetic tree based on 1196 core genes of clinical H. <t>influenzae</t> isolates and three well-studied laboratory strains (86-028NP, ATCC 10211, and ATCC 49247). The table displays the ID of people with CF (pwCF) and the capsule presence (typeable vs non-typeable). Note that one isolate had to be excluded from genetic analysis due to poor sequence qualities. (B) Genome size (in base pairs) of the clinical isolates, grouped by time window. (C) Average genome composition of clinical isolates, with genes classified as core (present in 100% of isolates), soft-core (90–99%), shell (15–89%), and cloud (0–14%). (D) Protease activity of clinical isolates measured using the azocasein assay. (E) Siderophore production of clinical isolates measured using the chrome azurol S (CAS) assay in ssBHI medium supplemented with 2,2’-bipyridine to a final concentration of 75 μM. (F) Biofilm formation under static growth conditions measured using the crystal violet assay. Asterisks denote significance levels: ***P < 0.001; **P < 0.01; *P < 0.05.
    Influenzae Isolates, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 799 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    1) Product Images from "Tracking eco-evolutionary dynamics among lung pathobiome members from children with cystic fibrosis"

    Article Title: Tracking eco-evolutionary dynamics among lung pathobiome members from children with cystic fibrosis

    Journal: bioRxiv

    doi: 10.64898/2026.01.29.702708

    (A) Phylogenetic tree based on 1196 core genes of clinical H. influenzae isolates and three well-studied laboratory strains (86-028NP, ATCC 10211, and ATCC 49247). The table displays the ID of people with CF (pwCF) and the capsule presence (typeable vs non-typeable). Note that one isolate had to be excluded from genetic analysis due to poor sequence qualities. (B) Genome size (in base pairs) of the clinical isolates, grouped by time window. (C) Average genome composition of clinical isolates, with genes classified as core (present in 100% of isolates), soft-core (90–99%), shell (15–89%), and cloud (0–14%). (D) Protease activity of clinical isolates measured using the azocasein assay. (E) Siderophore production of clinical isolates measured using the chrome azurol S (CAS) assay in ssBHI medium supplemented with 2,2’-bipyridine to a final concentration of 75 μM. (F) Biofilm formation under static growth conditions measured using the crystal violet assay. Asterisks denote significance levels: ***P < 0.001; **P < 0.01; *P < 0.05.
    Figure Legend Snippet: (A) Phylogenetic tree based on 1196 core genes of clinical H. influenzae isolates and three well-studied laboratory strains (86-028NP, ATCC 10211, and ATCC 49247). The table displays the ID of people with CF (pwCF) and the capsule presence (typeable vs non-typeable). Note that one isolate had to be excluded from genetic analysis due to poor sequence qualities. (B) Genome size (in base pairs) of the clinical isolates, grouped by time window. (C) Average genome composition of clinical isolates, with genes classified as core (present in 100% of isolates), soft-core (90–99%), shell (15–89%), and cloud (0–14%). (D) Protease activity of clinical isolates measured using the azocasein assay. (E) Siderophore production of clinical isolates measured using the chrome azurol S (CAS) assay in ssBHI medium supplemented with 2,2’-bipyridine to a final concentration of 75 μM. (F) Biofilm formation under static growth conditions measured using the crystal violet assay. Asterisks denote significance levels: ***P < 0.001; **P < 0.01; *P < 0.05.

    Techniques Used: Sequencing, Activity Assay, Azocasein Assay, Concentration Assay, Crystal Violet Assay

    Across time window supernatant assays reveal one donor effect (reduced P. aeruginosa supernatant toxicity at T3) and several receiver effects (T3 isolates cope better with supernatants than isolates from earlier time windows). Green boxplots in panels ( A), (C) and (E) show receiver effects for P. aeruginosa , S. aureus and H. influenzae isolates, respectively. Receiver effects were measured by exposing isolates from a specific time window T1, T2, or T3 to supernatants from respective donors (indicated on top of each panel) from all three time windows. Variation in growth across isolate time windows indicates that receivers differ and not the composition of the supernatants. Blue boxplots in panels (B), (D) and (F) show donor effects for P. aeruginosa , S. aureus and H. influenzae isolates, respectively. Donor effects were measured by exposing isolates from all time windows to supernatants sampled from a specific time window T1, T2, or T3. Variation in growth across supernatant time windows indicates that the composition of the supernatant (i.e., the donor) differs and not the receiving isolates. Receiver and donor effects were measured based on normalized growth (AUC relative to control condition) of isolates exposed to supernatants. We repeated the same analyses for the lag phase as an additional growth parameter (see Figure S8).
    Figure Legend Snippet: Across time window supernatant assays reveal one donor effect (reduced P. aeruginosa supernatant toxicity at T3) and several receiver effects (T3 isolates cope better with supernatants than isolates from earlier time windows). Green boxplots in panels ( A), (C) and (E) show receiver effects for P. aeruginosa , S. aureus and H. influenzae isolates, respectively. Receiver effects were measured by exposing isolates from a specific time window T1, T2, or T3 to supernatants from respective donors (indicated on top of each panel) from all three time windows. Variation in growth across isolate time windows indicates that receivers differ and not the composition of the supernatants. Blue boxplots in panels (B), (D) and (F) show donor effects for P. aeruginosa , S. aureus and H. influenzae isolates, respectively. Donor effects were measured by exposing isolates from all time windows to supernatants sampled from a specific time window T1, T2, or T3. Variation in growth across supernatant time windows indicates that the composition of the supernatant (i.e., the donor) differs and not the receiving isolates. Receiver and donor effects were measured based on normalized growth (AUC relative to control condition) of isolates exposed to supernatants. We repeated the same analyses for the lag phase as an additional growth parameter (see Figure S8).

    Techniques Used: Control

    Effect of protease production in P. aeruginosa on bacterial growth of S. aureus and H. influenzae estimated from generalized additive models (GAMs). (A) Relationship for S. aureus based on normalized lag phase data (log-transformed). (B) Relationship for H. influenzae based on normalized AUC (area under the curve) data. Both associations show the smoothed effect of protease activity with 95% confidence intervals (shaded ribbons), with points representing partial growth residuals. GAM models included hemolysis as categorical predictor and smooth terms for log-transformed biofilm formation, siderophore and protease production.
    Figure Legend Snippet: Effect of protease production in P. aeruginosa on bacterial growth of S. aureus and H. influenzae estimated from generalized additive models (GAMs). (A) Relationship for S. aureus based on normalized lag phase data (log-transformed). (B) Relationship for H. influenzae based on normalized AUC (area under the curve) data. Both associations show the smoothed effect of protease activity with 95% confidence intervals (shaded ribbons), with points representing partial growth residuals. GAM models included hemolysis as categorical predictor and smooth terms for log-transformed biofilm formation, siderophore and protease production.

    Techniques Used: Transformation Assay, Activity Assay



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    (A) Phylogenetic tree based on 1196 core genes of clinical H. <t>influenzae</t> isolates and three well-studied laboratory strains (86-028NP, ATCC 10211, and ATCC 49247). The table displays the ID of people with CF (pwCF) and the capsule presence (typeable vs non-typeable). Note that one isolate had to be excluded from genetic analysis due to poor sequence qualities. (B) Genome size (in base pairs) of the clinical isolates, grouped by time window. (C) Average genome composition of clinical isolates, with genes classified as core (present in 100% of isolates), soft-core (90–99%), shell (15–89%), and cloud (0–14%). (D) Protease activity of clinical isolates measured using the azocasein assay. (E) Siderophore production of clinical isolates measured using the chrome azurol S (CAS) assay in ssBHI medium supplemented with 2,2’-bipyridine to a final concentration of 75 μM. (F) Biofilm formation under static growth conditions measured using the crystal violet assay. Asterisks denote significance levels: ***P < 0.001; **P < 0.01; *P < 0.05.
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    (A) Phylogenetic tree based on 1196 core genes of clinical H. <t>influenzae</t> isolates and three well-studied laboratory strains (86-028NP, ATCC 10211, and ATCC 49247). The table displays the ID of people with CF (pwCF) and the capsule presence (typeable vs non-typeable). Note that one isolate had to be excluded from genetic analysis due to poor sequence qualities. (B) Genome size (in base pairs) of the clinical isolates, grouped by time window. (C) Average genome composition of clinical isolates, with genes classified as core (present in 100% of isolates), soft-core (90–99%), shell (15–89%), and cloud (0–14%). (D) Protease activity of clinical isolates measured using the azocasein assay. (E) Siderophore production of clinical isolates measured using the chrome azurol S (CAS) assay in ssBHI medium supplemented with 2,2’-bipyridine to a final concentration of 75 μM. (F) Biofilm formation under static growth conditions measured using the crystal violet assay. Asterisks denote significance levels: ***P < 0.001; **P < 0.01; *P < 0.05.
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    Image Search Results


    (A) Phylogenetic tree based on 1196 core genes of clinical H. influenzae isolates and three well-studied laboratory strains (86-028NP, ATCC 10211, and ATCC 49247). The table displays the ID of people with CF (pwCF) and the capsule presence (typeable vs non-typeable). Note that one isolate had to be excluded from genetic analysis due to poor sequence qualities. (B) Genome size (in base pairs) of the clinical isolates, grouped by time window. (C) Average genome composition of clinical isolates, with genes classified as core (present in 100% of isolates), soft-core (90–99%), shell (15–89%), and cloud (0–14%). (D) Protease activity of clinical isolates measured using the azocasein assay. (E) Siderophore production of clinical isolates measured using the chrome azurol S (CAS) assay in ssBHI medium supplemented with 2,2’-bipyridine to a final concentration of 75 μM. (F) Biofilm formation under static growth conditions measured using the crystal violet assay. Asterisks denote significance levels: ***P < 0.001; **P < 0.01; *P < 0.05.

    Journal: bioRxiv

    Article Title: Tracking eco-evolutionary dynamics among lung pathobiome members from children with cystic fibrosis

    doi: 10.64898/2026.01.29.702708

    Figure Lengend Snippet: (A) Phylogenetic tree based on 1196 core genes of clinical H. influenzae isolates and three well-studied laboratory strains (86-028NP, ATCC 10211, and ATCC 49247). The table displays the ID of people with CF (pwCF) and the capsule presence (typeable vs non-typeable). Note that one isolate had to be excluded from genetic analysis due to poor sequence qualities. (B) Genome size (in base pairs) of the clinical isolates, grouped by time window. (C) Average genome composition of clinical isolates, with genes classified as core (present in 100% of isolates), soft-core (90–99%), shell (15–89%), and cloud (0–14%). (D) Protease activity of clinical isolates measured using the azocasein assay. (E) Siderophore production of clinical isolates measured using the chrome azurol S (CAS) assay in ssBHI medium supplemented with 2,2’-bipyridine to a final concentration of 75 μM. (F) Biofilm formation under static growth conditions measured using the crystal violet assay. Asterisks denote significance levels: ***P < 0.001; **P < 0.01; *P < 0.05.

    Article Snippet: We examined the phylogenetic relationship among the 20 sequenced clinical H. influenzae isolates (one isolate was lost due to poor sequencing quality) and three laboratory strains (ATCC 49247, ATCC 10211, and 86-028NP) based on 1196 core genes ( ).

    Techniques: Sequencing, Activity Assay, Azocasein Assay, Concentration Assay, Crystal Violet Assay

    Across time window supernatant assays reveal one donor effect (reduced P. aeruginosa supernatant toxicity at T3) and several receiver effects (T3 isolates cope better with supernatants than isolates from earlier time windows). Green boxplots in panels ( A), (C) and (E) show receiver effects for P. aeruginosa , S. aureus and H. influenzae isolates, respectively. Receiver effects were measured by exposing isolates from a specific time window T1, T2, or T3 to supernatants from respective donors (indicated on top of each panel) from all three time windows. Variation in growth across isolate time windows indicates that receivers differ and not the composition of the supernatants. Blue boxplots in panels (B), (D) and (F) show donor effects for P. aeruginosa , S. aureus and H. influenzae isolates, respectively. Donor effects were measured by exposing isolates from all time windows to supernatants sampled from a specific time window T1, T2, or T3. Variation in growth across supernatant time windows indicates that the composition of the supernatant (i.e., the donor) differs and not the receiving isolates. Receiver and donor effects were measured based on normalized growth (AUC relative to control condition) of isolates exposed to supernatants. We repeated the same analyses for the lag phase as an additional growth parameter (see Figure S8).

    Journal: bioRxiv

    Article Title: Tracking eco-evolutionary dynamics among lung pathobiome members from children with cystic fibrosis

    doi: 10.64898/2026.01.29.702708

    Figure Lengend Snippet: Across time window supernatant assays reveal one donor effect (reduced P. aeruginosa supernatant toxicity at T3) and several receiver effects (T3 isolates cope better with supernatants than isolates from earlier time windows). Green boxplots in panels ( A), (C) and (E) show receiver effects for P. aeruginosa , S. aureus and H. influenzae isolates, respectively. Receiver effects were measured by exposing isolates from a specific time window T1, T2, or T3 to supernatants from respective donors (indicated on top of each panel) from all three time windows. Variation in growth across isolate time windows indicates that receivers differ and not the composition of the supernatants. Blue boxplots in panels (B), (D) and (F) show donor effects for P. aeruginosa , S. aureus and H. influenzae isolates, respectively. Donor effects were measured by exposing isolates from all time windows to supernatants sampled from a specific time window T1, T2, or T3. Variation in growth across supernatant time windows indicates that the composition of the supernatant (i.e., the donor) differs and not the receiving isolates. Receiver and donor effects were measured based on normalized growth (AUC relative to control condition) of isolates exposed to supernatants. We repeated the same analyses for the lag phase as an additional growth parameter (see Figure S8).

    Article Snippet: We examined the phylogenetic relationship among the 20 sequenced clinical H. influenzae isolates (one isolate was lost due to poor sequencing quality) and three laboratory strains (ATCC 49247, ATCC 10211, and 86-028NP) based on 1196 core genes ( ).

    Techniques: Control

    Effect of protease production in P. aeruginosa on bacterial growth of S. aureus and H. influenzae estimated from generalized additive models (GAMs). (A) Relationship for S. aureus based on normalized lag phase data (log-transformed). (B) Relationship for H. influenzae based on normalized AUC (area under the curve) data. Both associations show the smoothed effect of protease activity with 95% confidence intervals (shaded ribbons), with points representing partial growth residuals. GAM models included hemolysis as categorical predictor and smooth terms for log-transformed biofilm formation, siderophore and protease production.

    Journal: bioRxiv

    Article Title: Tracking eco-evolutionary dynamics among lung pathobiome members from children with cystic fibrosis

    doi: 10.64898/2026.01.29.702708

    Figure Lengend Snippet: Effect of protease production in P. aeruginosa on bacterial growth of S. aureus and H. influenzae estimated from generalized additive models (GAMs). (A) Relationship for S. aureus based on normalized lag phase data (log-transformed). (B) Relationship for H. influenzae based on normalized AUC (area under the curve) data. Both associations show the smoothed effect of protease activity with 95% confidence intervals (shaded ribbons), with points representing partial growth residuals. GAM models included hemolysis as categorical predictor and smooth terms for log-transformed biofilm formation, siderophore and protease production.

    Article Snippet: We examined the phylogenetic relationship among the 20 sequenced clinical H. influenzae isolates (one isolate was lost due to poor sequencing quality) and three laboratory strains (ATCC 49247, ATCC 10211, and 86-028NP) based on 1196 core genes ( ).

    Techniques: Transformation Assay, Activity Assay