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Article: Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells.

Mellis, Ian A / Bodkin, Nicholas / Melzer, Madeline E / Goyal, Yogesh

bioRxiv : the preprint server for biology

2023

Abstract: Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which ...

Abstract	Cells and tissues have a remarkable ability to adapt to genetic perturbations via a variety of molecular mechanisms. Nonsense-induced transcriptional compensation, a form of transcriptional adaptation, has recently emerged as one such mechanism, in which nonsense mutations in a gene can trigger upregulation of related genes, possibly conferring robustness at cellular and organismal levels. However, beyond a handful of developmental contexts and curated sets of genes, to date, no comprehensive genome-wide investigation of this behavior has been undertaken for mammalian cell types and contexts. Moreover, how the regulatory-level effects of inherently stochastic compensatory gene networks contribute to phenotypic penetrance in single cells remains unclear. Here we combine computational analysis of existing datasets with stochastic mathematical modeling and machine learning to uncover the widespread prevalence of transcriptional adaptation in mammalian systems and the diverse single-cell manifestations of minimal compensatory gene networks. Regulon gene expression analysis of a pooled single-cell genetic perturbation dataset recapitulates important model predictions. Our integrative approach uncovers several putative hits-genes demonstrating possible transcriptional adaptation-to follow up on experimentally, and provides a formal quantitative framework to test and refine models of transcriptional adaptation.
Language	English
Publishing date	2023-11-30
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.08.14.553318
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Article ; Online: BRAND: a platform for closed-loop experiments with deep network models.

Ali, Yahia H / Bodkin, Kevin / Rigotti-Thompson, Mattia / Patel, Kushant / Card, Nicholas S / Bhaduri, Bareesh / Nason-Tomaszewski, Samuel R / Mifsud, Domenick M / Hou, Xianda / Nicolas, Claire / Allcroft, Shane / Hochberg, Leigh R / Au Yong, Nicholas / Stavisky, Sergey D / Miller, Lee E / Brandman, David M / Pandarinath, Chethan

Journal of neural engineering

2024 Volume 21, Issue 2

Abstract: Objective. ...

Abstract	Objective.
MeSH term(s)	Humans ; Neural Networks, Computer ; Brain-Computer Interfaces ; Neurosciences
Language	English
Publishing date	2024-04-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2170901-4
ISSN	1741-2552 ; 1741-2560
ISSN (online)	1741-2552
ISSN	1741-2560
DOI	10.1088/1741-2552/ad3b3a
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Article: BRAND: A platform for closed-loop experiments with deep network models.

Ali, Yahia H / Bodkin, Kevin / Rigotti-Thompson, Mattia / Patel, Kushant / Card, Nicholas S / Bhaduri, Bareesh / Nason-Tomaszewski, Samuel R / Mifsud, Domenick M / Hou, Xianda / Nicolas, Claire / Allcroft, Shane / Hochberg, Leigh R / Yong, Nicholas Au / Stavisky, Sergey D / Miller, Lee E / Brandman, David M / Pandarinath, Chethan

bioRxiv : the preprint server for biology

2023

Abstract: Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing real-time ... ...

Abstract	Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing real-time frameworks. Researchers need a platform that fully supports high-level languages for running ANNs (e.g., Python and Julia) while maintaining support for languages that are critical for low-latency data acquisition and processing (e.g., C and C++). To address these needs, we introduce the Backend for Realtime Asynchronous Neural Decoding (BRAND). BRAND comprises Linux processes, termed
Language	English
Publishing date	2023-08-12
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.08.08.552473
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Article ; Online: Systematic comparison of published host gene expression signatures for bacterial/viral discrimination.

Bodkin, Nicholas / Ross, Melissa / McClain, Micah T / Ko, Emily R / Woods, Christopher W / Ginsburg, Geoffrey S / Henao, Ricardo / Tsalik, Ephraim L

Genome medicine

2022 Volume 14, Issue 1, Page(s) 18

Abstract: Background: Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little ... ...

Abstract	Background: Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another. Methods: This systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies. Results: Signature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69-0.97 for viral classification. Signature size varied (1-398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in some pediatric populations (3 months-1 year and 2-11 years) compared to the adult population for both bacterial infection (73% and 70% vs. 82%, respectively; P < .001) and viral infection (80% and 79% vs. 88%, respectively; P < .001). We did not observe classification differences based on illness severity as defined by ICU admission for bacterial or viral infections. The median AUC across all signatures for COVID-19 classification was 0.80 compared to 0.83 for viral classification in the same datasets. Conclusions: In this systematic comparison of 28 host gene expression signatures, we observed differences based on a signature's size and characteristics of the validation population, including age and infection type. However, populations used for signature discovery did not impact performance, underscoring the redundancy among many of these signatures. Furthermore, differential performance in specific populations may only be observable through this type of large-scale validation.
MeSH term(s)	Adult ; Bacterial Infections/diagnosis ; Bacterial Infections/epidemiology ; Bacterial Infections/genetics ; Biomarkers/analysis ; COVID-19/diagnosis ; COVID-19/genetics ; Child ; Cohort Studies ; Datasets as Topic/statistics & numerical data ; Diagnosis, Differential ; Gene Expression Profiling/statistics & numerical data ; Genetic Association Studies/statistics & numerical data ; Host-Pathogen Interactions/genetics ; Humans ; Publications/statistics & numerical data ; SARS-CoV-2/pathogenicity ; Transcriptome ; Validation Studies as Topic ; Virus Diseases/diagnosis ; Virus Diseases/epidemiology ; Virus Diseases/genetics
Chemical Substances	Biomarkers
Language	English
Publishing date	2022-02-21
Publishing country	England
Document type	Comparative Study ; Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2484394-5
ISSN	1756-994X ; 1756-994X
ISSN (online)	1756-994X
ISSN	1756-994X
DOI	10.1186/s13073-022-01025-x
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Article ; Online: Neurosurgery in Aberdeen Royal Infirmary c. 1920-c.1940: knowledge, skills and styles.

Newall, Nicola / Bodkin, Peter

The journal of the Royal College of Physicians of Edinburgh

2019 Volume 49, Issue 1, Page(s) 70–77

Abstract: ... of Martin Nichols as its first full-time neurosurgeon. Despite there being no formal neurosurgical ward or ...

Abstract	A neurosurgical unit was established in Aberdeen Royal Infirmary (ARI) in 1948 with the appointment of Martin Nichols as its first full-time neurosurgeon. Despite there being no formal neurosurgical ward or specialist dedicated to neurosurgery in ARI prior to this, a number of neurosurgical procedures were undertaken between 1920 and 1940. From 1923 to 1932, the procedures were predominantly cranial and were performed by general surgeons. The operations evolved in 1933 to include the spine and peripheral nerves after the arrival of Sir James Learmonth. This paper chronicles the development of surgical neurology at the ARI in the 30 years preceding a formal unit. It considers the factors and background that enabled neurosurgical practices to be undertaken and led to evolution of neurosurgery from general surgery.
MeSH term(s)	History, 20th Century ; Humans ; Neurosurgery/history ; Neurosurgical Procedures/history ; Scotland ; Societies, Medical/history
Language	English
Publishing date	2019-03-19
Publishing country	Scotland
Document type	Historical Article ; Journal Article
ZDB-ID	2866363-9
ISSN	2042-8189 ; 0953-0932
ISSN (online)	2042-8189
ISSN	0953-0932
DOI	10.4997/JRCPE.2019.115
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Zs.A 3088 -Suppl.-: Show issues

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Article ; Online: MN-166 (ibudilast) in amyotrophic lateral sclerosis in a Phase IIb/III study: COMBAT-ALS study design.

Oskarsson, Björn / Maragakis, Nicholas / Bedlack, Richard S / Goyal, Namita / Meyer, Jenny A / Genge, Angela / Bodkin, Cynthia / Maiser, Samuel / Staff, Nathan / Zinman, Lorne / Olney, Nicholas / Turnbull, John / Brooks, Benjamin Rix / Klonowski, Emelia / Makhay, Malath / Yasui, Seiichi / Matsuda, Kazuko

Neurodegenerative disease management

2021 Volume 11, Issue 6, Page(s) 431–443

Abstract: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with motor neuron loss as a defining feature. Despite significant effort, therapeutic breakthroughs have been modest. MN-166 (ibudilast) has demonstrated neuroprotective action by various ...

Abstract	Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with motor neuron loss as a defining feature. Despite significant effort, therapeutic breakthroughs have been modest. MN-166 (ibudilast) has demonstrated neuroprotective action by various mechanisms: inhibition of proinflammatory cytokines and macrophage migration inhibitory factor, phosphodiesterase inhibition, and attenuation of glial cell activation in models of ALS. Early-phase studies suggest that MN-166 may improve survival outcomes and slow disease progression in patients with ALS. This article describes the rationale and design of COMBAT-ALS, an ongoing randomized, double-blind, placebo-controlled, multicenter Phase IIb/III study in ALS. This study is designed to evaluate the pharmacokinetics, safety and tolerability and assess the efficacy of MN-166 on function, muscle strength, quality of life and survival in ALS.
MeSH term(s)	Amyotrophic Lateral Sclerosis/drug therapy ; Double-Blind Method ; Humans ; Neurodegenerative Diseases ; Pyridines ; Quality of Life
Chemical Substances	Pyridines ; ibudilast (M0TTH61XC5)
Language	English
Publishing date	2021-11-24
Publishing country	England
Document type	Journal Article ; Multicenter Study ; Randomized Controlled Trial ; Research Support, Non-U.S. Gov't
ZDB-ID	2608846-0
ISSN	1758-2032 ; 1758-2024
ISSN (online)	1758-2032
ISSN	1758-2024
DOI	10.2217/nmt-2021-0042
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Article ; Online: Neurosurgery in Aberdeen Royal Infirmary c. 1920–c.1940

Nicola Newall / Peter Bodkin

The Journal of the Royal College of Physicians of Edinburgh, Vol 49, Iss 1, Pp 70-

knowledge, skills and styles

2019 Volume 77

Abstract: ... of Martin Nichols as its first full-time neurosurgeon. Despite there being no formal neurosurgical ward or ...

Abstract	A neurosurgical unit was established in Aberdeen Royal Infirmary (ARI) in 1948 with the appointment of Martin Nichols as its first full-time neurosurgeon. Despite there being no formal neurosurgical ward or specialist dedicated to neurosurgery in ARI prior to this, a number of neurosurgical procedures were undertaken between 1920 and 1940. From 1923 to 1932, the procedures were predominantly cranial and were performed by general surgeons. The operations evolved in 1933 to include the spine and peripheral nerves after the arrival of Sir James Learmonth. This paper chronicles the development of surgical neurology at the ARI in the 30 years preceding a formal unit. It considers the factors and background that enabled neurosurgical practices to be undertaken and led to evolution of neurosurgery from general surgery.
Keywords	Aberdeen Royal Infirmary ; Henry Gray ; James Learmonth ; neurosurgery ; William Anderson ; Medicine (General) ; R5-920
Subject code	941
Language	English
Publishing date	2019-03-01T00:00:00Z
Publisher	Royal College of Physicians of Edinburgh
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Systematic comparison of published host gene expression signatures for bacterial/viral discrimination

Nicholas Bodkin / Melissa Ross / Micah T. McClain / Emily R. Ko / Christopher W. Woods / Geoffrey S. Ginsburg / Ricardo Henao / Ephraim L. Tsalik

Genome Medicine, Vol 14, Iss 1, Pp 1-

2022 Volume 14

Abstract: Abstract Background Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little ... ...

Abstract	Abstract Background Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another. Methods This systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies. Results Signature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69–0.97 for viral classification. Signature size varied (1–398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in some pediatric populations (3 months–1 year and 2–11 years) compared to the adult population for both bacterial infection (73% and 70% vs. 82%, respectively; P < .001) and viral infection (80% and 79% vs. 88%, respectively; P < .001). We did not observe classification differences based on illness severity as defined by ICU admission for bacterial or viral infections. The median AUC across all signatures for COVID-19 classification was 0.80 compared to 0.83 for viral classification in the same datasets. Conclusions In this systematic comparison of 28 host gene expression signatures, we observed differences based on a signature’s size and characteristics of the validation population, including age and infection type. However, populations used for signature ...
Keywords	Biomarkers ; Infectious disease ; Diagnostics ; Gene expression ; Machine learning ; Medicine ; R ; Genetics ; QH426-470
Subject code	572
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Diverse clonal fates emerge upon drug treatment of homogeneous cancer cells.

Goyal, Yogesh / Busch, Gianna T / Pillai, Maalavika / Li, Jingxin / Boe, Ryan H / Grody, Emanuelle I / Chelvanambi, Manoj / Dardani, Ian P / Emert, Benjamin / Bodkin, Nicholas / Braun, Jonas / Fingerman, Dylan / Kaur, Amanpreet / Jain, Naveen / Ravindran, Pavithran T / Mellis, Ian A / Kiani, Karun / Alicea, Gretchen M / Fane, Mitchell E /

Ahmed, Syeda Subia / Li, Haiyin / Chen, Yeqing / Chai, Cedric / Kaster, Jessica / Witt, Russell G / Lazcano, Rossana / Ingram, Davis R / Johnson, Sarah B / Wani, Khalida / Dunagin, Margaret C / Lazar, Alexander J / Weeraratna, Ashani T / Wargo, Jennifer A / Herlyn, Meenhard / Raj, Arjun

Nature

2023 Volume 620, Issue 7974, Page(s) 651–659

Abstract: Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those ... ...

Abstract	Even among genetically identical cancer cells, resistance to therapy frequently emerges from a small subset of those cells
MeSH term(s)	Humans ; Clone Cells/drug effects ; Clone Cells/metabolism ; Clone Cells/pathology ; DNA Barcoding, Taxonomic ; Drug Resistance, Neoplasm/drug effects ; Drug Resistance, Neoplasm/genetics ; Neoplasms/drug therapy ; Neoplasms/genetics ; Neoplasms/pathology ; RNA-Seq ; Single-Cell Gene Expression Analysis ; Tumor Cells, Cultured ; Antineoplastic Agents/pharmacology
Chemical Substances	Antineoplastic Agents
Language	English
Publishing date	2023-07-19
Publishing country	England
Document type	Journal Article
ZDB-ID	120714-3
ISSN	1476-4687 ; 0028-0836
ISSN (online)	1476-4687
ISSN	0028-0836
DOI	10.1038/s41586-023-06342-8
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Zs.A 26: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
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Article ; Online: Evaluation of M2-like macrophage enrichment after diffuse traumatic brain injury through transient interleukin-4 expression from engineered mesenchymal stromal cells.

Enam, Syed Faaiz / Kader, Sajidur Rahman / Bodkin, Nicholas / Lyon, Johnathan G / Calhoun, Mark / Azrak, Cesar / Tiwari, Pooja Munnilal / Vanover, Daryll / Wang, Haichen / Santangelo, Philip J / Bellamkonda, Ravi Venkat

Journal of neuroinflammation

2020 Volume 17, Issue 1, Page(s) 197

Abstract: Background: Appropriately modulating inflammation after traumatic brain injury (TBI) may prevent disabilities for the millions of those inflicted annually. In TBI, cellular mediators of inflammation, including macrophages and microglia, possess a range ... ...

Abstract	Background: Appropriately modulating inflammation after traumatic brain injury (TBI) may prevent disabilities for the millions of those inflicted annually. In TBI, cellular mediators of inflammation, including macrophages and microglia, possess a range of phenotypes relevant for an immunomodulatory therapeutic approach. It is thought that early phenotypic modulation of these cells will have a cascading healing effect. In fact, an anti-inflammatory, "M2-like" macrophage phenotype after TBI has been associated with neurogenesis, axonal regeneration, and improved white matter integrity (WMI). There already exist clinical trials seeking an M2-like bias through mesenchymal stem/stromal cells (MSCs). However, MSCs do not endogenously synthesize key signals that induce robust M2-like phenotypes such as interleukin-4 (IL-4). Methods: To enrich M2-like macrophages in a clinically relevant manner, we augmented MSCs with synthetic IL-4 mRNA to transiently express IL-4. These IL-4 expressing MSCs (IL-4 MSCs) were characterized for expression and functionality and then delivered in a modified mouse TBI model of closed head injury. Groups were assessed for functional deficits and MR imaging. Brain tissue was analyzed through flow cytometry, multi-plex ELISA, qPCR, histology, and RNA sequencing. Results: We observed that IL-4 MSCs indeed induce a robust M2-like macrophage phenotype and promote anti-inflammatory gene expression after TBI. However, here we demonstrate that acute enrichment of M2-like macrophages did not translate to improved functional or histological outcomes, or improvements in WMI on MR imaging. To further understand whether dysfunctional pathways underlie the lack of therapeutic effect, we report transcriptomic analysis of injured and treated brains. Through this, we discovered that inflammation persists despite acute enrichment of M2-like macrophages in the brain. Conclusion: The results demonstrate that MSCs can be engineered to induce a stronger M2-like macrophage response in vivo. However, they also suggest that acute enrichment of only M2-like macrophages after diffuse TBI cannot orchestrate neurogenesis, axonal regeneration, or improve WMI. Here, we also discuss our modified TBI model and methods to assess severity, behavioral studies, and propose that IL-4 expressing MSCs may also have relevance in other cavitary diseases or in improving biomaterial integration into tissues.
MeSH term(s)	Animals ; Brain Injuries, Traumatic/metabolism ; Disease Models, Animal ; Inflammation/metabolism ; Interleukin-4/metabolism ; Macrophages/metabolism ; Male ; Mesenchymal Stem Cells/metabolism ; Mice ; Microglia/metabolism
Chemical Substances	Interleukin-4 (207137-56-2)
Language	English
Publishing date	2020-06-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2156455-3
ISSN	1742-2094 ; 1742-2094
ISSN (online)	1742-2094
ISSN	1742-2094
DOI	10.1186/s12974-020-01860-y
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