{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/125673"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/125673","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Development and application of tools to visualize and assess the roles of specific biomolecules in cells","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-08-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-08-01","abstract_has_math":false,"creators":["Brunet Torres, Melanie Ann"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Chemical Engineering","degree_department":null,"school":null,"contributors":["Kraft, Mary L","Pogorelov, Taras V","Guillermier, Christelle","Brooke, Christopher B"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-06-26","date_published":"2024-06-26","updated_at":"2026-07-22T22:25:02Z","subjects":["Secondary Ion Mass Spectrometry","Nanosims","Depth Profiling","Biomolecules","Morphology Reconstruction","Secondary Electron Images","Molecular Dynamics","Influenza Virus","Lipids","Cell Membrane","Cholesterol","Matlab"],"languages":["en","eng"],"rights":["© 2024 Melanie Ann Brunet Torres"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/125673","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kraft, Mary L","Pogorelov, Taras V","Guillermier, Christelle","Brooke, Christopher B"]},{"key":"dc:creator","label":"Author","values":["Brunet Torres, Melanie Ann"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-06-26","2024-08"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Chemical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Secondary Ion Mass Spectrometry","Nanosims","Depth Profiling","Biomolecules","Morphology Reconstruction","Secondary Electron Images","Molecular Dynamics","Influenza Virus","Lipids","Cell Membrane","Cholesterol","Matlab"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["© 2024 Melanie Ann Brunet Torres"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/125673"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-08-01","The student, Melanie Brunet Torres, accepted the attached license on 2024-06-24 at 15:42.","The student, Melanie Brunet Torres, submitted this Dissertation for approval on 2024-06-24 at 16:08.","This Dissertation was approved for publication on 2024-06-26 at 16:29.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20868 on 2025-02-04 at 21:15:46","Experimental and computational tools are essential for understanding the complex interactions of biomolecules within cells. Visualizing the spatial distributions of biomolecules and performing molecular dynamics (MD) simulations allows us to probe the roles of biomolecules of interest, such as sphingolipids and cholesterol, at both microscopic and atomic levels. In this study, we applied both experimental and computational tools to visualize the spatial distributions of biomolecules within mammalian cells and to investigate the interactions between the influenza virus fusion peptide and the host cell membrane, at the atomic level. By integrating these approaches, we gained valuable insights into the spatial distributions of biomolecules in cellular processes and the molecular mechanisms underlying viral infection. Visualizing the spatial distributions of biomolecules within cells provides information about their functions and diverse roles in cellular processes. High-resolution secondary ion mass spectrometry (NanoSIMS) depth profiling enables imaging these distributions, generating a series of two-dimensional (2D) images of the analyzed region. These images can then be processed to produce a three-dimensional (3D) image of the intracellular distributions of the analyzed biomolecules. However, because this process does not account for cell topography, the resulting 3D images are distorted in the z-direction, hindering image interpretation. To address this, we developed a new depth correction tool for 3D NanoSIMS depth profiling images of cells. This tool accurately reconstructs the cell morphology by accounting for sample topography and small surface changes induced by differential sputter rate, using pixel intensities from secondary electron and secondary ion images. Then the heights encoded in these morphonology reconstructions are used to shift the z-positions of each voxel (depth correct) in the 3D NanoSIMS image. The accuracy of this depth correction tool was validated by comparing AFM topography data with the reconstructed cell morphology, achieving an average accuracy of 90%. This marks a significant improvement over uncorrected 3D NanoSIMS images. Moreover, we extended this tool to reconstruct cell morphologies in the absence of secondary electron images, achieving accuracies as high as 98% when compared to reconstructions using secondary electron images. We applied this depth correction tool to visualize the distributions of various biomolecules within cells. Specifically, we visualized the spatial distribution of 15N-sphingolipids, 18O-cholesterol, 15N-labeled RNA, and 13C-labeled DNA in mammalian cells, in addition to the incorporation of 15N-nitrate and 13C-carbonate in algae cells. Depth correction notably improved the visualization of intracellular features containing these labels. This tool also facilitated the assessment of colocalization between rare isotope-labeled biomolecules. A significant advantage of this depth correction tool is its capability to generate depth-corrected 3D NanoSIMS images for both new and existing datasets of cells, even without correlated topography data. With this capability, we anticipate an improved understanding of biomolecule distributions within cells. Influenza A virus remains a significant global health threat, causing high mortality and morbidity despite existing antiviral drugs and vaccines. Identification of the host cell components that promote infection when present at high levels but sustain normal cell function at lower levels could lead to the development of new types of antiviral therapeutics with pan-strain potency and decreased drug resistance. Notably, sphingolipids and cholesterol have emerged as potential targets, given their correlation with influenza virus replication and infectivity. However, the mechanisms by which these components promote influenza virus infection remain poorly understood. Of particular interest is the role of the influenza virus fusion peptide (FP), which mediates membrane fusion during viral entry. Although the direct contact of the FP with the host cell membrane is essential for fusion, the specific interactions underlying this process are not fully understood. To address this, we performed MD simulations to investigate the FP insertion into membranes with varying lipid compositions. Our findings revealed that membranes containing cholesterol promoted the insertion of the FP into the host cell membrane, whereas membranes lacking cholesterol were more resistant to insertion of the FP. Notably, in all systems where the FP inserted, the membrane-bound configuration resulted in the N-terminal helix inserting deeper than the C-terminal helix. This suggests that residues in the N-terminal helix are primarily responsible for hydrophobic interactions and anchoring, while residues in the C-terminal helix reinforce this anchoring through amphiphilic interactions. These findings may offer valuable insights into the critical molecular mechanisms exploited by the influenza virus for efficient viral infection. Moreover, they may pave the way for the development of fusion blocker antivirals targeting critical host cell components, potentially offering novel strategies for fighting viral infections."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Development and application of tools to visualize and assess the roles of specific biomolecules in cells"]}]}],"canonical_facts":{"dc:contributor":["Kraft, Mary L","Pogorelov, Taras V","Guillermier, Christelle","Brooke, Christopher B"],"dc:creator":["Brunet Torres, Melanie Ann"],"dc:date":["2024-06-26","2024-08"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-08-01","The student, Melanie Brunet Torres, accepted the attached license on 2024-06-24 at 15:42.","The student, Melanie Brunet Torres, submitted this Dissertation for approval on 2024-06-24 at 16:08.","This Dissertation was approved for publication on 2024-06-26 at 16:29.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20868 on 2025-02-04 at 21:15:46","Experimental and computational tools are essential for understanding the complex interactions of biomolecules within cells. Visualizing the spatial distributions of biomolecules and performing molecular dynamics (MD) simulations allows us to probe the roles of biomolecules of interest, such as sphingolipids and cholesterol, at both microscopic and atomic levels. In this study, we applied both experimental and computational tools to visualize the spatial distributions of biomolecules within mammalian cells and to investigate the interactions between the influenza virus fusion peptide and the host cell membrane, at the atomic level. By integrating these approaches, we gained valuable insights into the spatial distributions of biomolecules in cellular processes and the molecular mechanisms underlying viral infection. Visualizing the spatial distributions of biomolecules within cells provides information about their functions and diverse roles in cellular processes. High-resolution secondary ion mass spectrometry (NanoSIMS) depth profiling enables imaging these distributions, generating a series of two-dimensional (2D) images of the analyzed region. These images can then be processed to produce a three-dimensional (3D) image of the intracellular distributions of the analyzed biomolecules. However, because this process does not account for cell topography, the resulting 3D images are distorted in the z-direction, hindering image interpretation. To address this, we developed a new depth correction tool for 3D NanoSIMS depth profiling images of cells. This tool accurately reconstructs the cell morphology by accounting for sample topography and small surface changes induced by differential sputter rate, using pixel intensities from secondary electron and secondary ion images. Then the heights encoded in these morphonology reconstructions are used to shift the z-positions of each voxel (depth correct) in the 3D NanoSIMS image. The accuracy of this depth correction tool was validated by comparing AFM topography data with the reconstructed cell morphology, achieving an average accuracy of 90%. This marks a significant improvement over uncorrected 3D NanoSIMS images. Moreover, we extended this tool to reconstruct cell morphologies in the absence of secondary electron images, achieving accuracies as high as 98% when compared to reconstructions using secondary electron images. We applied this depth correction tool to visualize the distributions of various biomolecules within cells. Specifically, we visualized the spatial distribution of 15N-sphingolipids, 18O-cholesterol, 15N-labeled RNA, and 13C-labeled DNA in mammalian cells, in addition to the incorporation of 15N-nitrate and 13C-carbonate in algae cells. Depth correction notably improved the visualization of intracellular features containing these labels. This tool also facilitated the assessment of colocalization between rare isotope-labeled biomolecules. A significant advantage of this depth correction tool is its capability to generate depth-corrected 3D NanoSIMS images for both new and existing datasets of cells, even without correlated topography data. With this capability, we anticipate an improved understanding of biomolecule distributions within cells. Influenza A virus remains a significant global health threat, causing high mortality and morbidity despite existing antiviral drugs and vaccines. Identification of the host cell components that promote infection when present at high levels but sustain normal cell function at lower levels could lead to the development of new types of antiviral therapeutics with pan-strain potency and decreased drug resistance. Notably, sphingolipids and cholesterol have emerged as potential targets, given their correlation with influenza virus replication and infectivity. However, the mechanisms by which these components promote influenza virus infection remain poorly understood. Of particular interest is the role of the influenza virus fusion peptide (FP), which mediates membrane fusion during viral entry. Although the direct contact of the FP with the host cell membrane is essential for fusion, the specific interactions underlying this process are not fully understood. To address this, we performed MD simulations to investigate the FP insertion into membranes with varying lipid compositions. Our findings revealed that membranes containing cholesterol promoted the insertion of the FP into the host cell membrane, whereas membranes lacking cholesterol were more resistant to insertion of the FP. Notably, in all systems where the FP inserted, the membrane-bound configuration resulted in the N-terminal helix inserting deeper than the C-terminal helix. This suggests that residues in the N-terminal helix are primarily responsible for hydrophobic interactions and anchoring, while residues in the C-terminal helix reinforce this anchoring through amphiphilic interactions. These findings may offer valuable insights into the critical molecular mechanisms exploited by the influenza virus for efficient viral infection. Moreover, they may pave the way for the development of fusion blocker antivirals targeting critical host cell components, potentially offering novel strategies for fighting viral infections."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/125673"],"dc:language":["en","eng"],"dc:rights":["© 2024 Melanie Ann Brunet Torres"],"dc:subject":["Secondary Ion Mass Spectrometry","Nanosims","Depth Profiling","Biomolecules","Morphology Reconstruction","Secondary Electron Images","Molecular Dynamics","Influenza Virus","Lipids","Cell Membrane","Cholesterol","Matlab"],"dc:title":["Development and application of tools to visualize and assess the roles of specific biomolecules in cells"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Chemical Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:02Z"}