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BEGIN:VEVENT
SUMMARY:Shiva Razavi (MIT)
DTSTART:20230627T150000Z
DTEND:20230627T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/1
DESCRIPTION:Title: Autocatalytic base editing for RNA-responsive translational cont
rol\nby Shiva Razavi (MIT) as part of Seminar on Biological Control Sy
stems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/1/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Enoch Yeung (UCSB)
DTSTART:20231024T150000Z
DTEND:20231024T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/2
DESCRIPTION:Title: Data-Driven State Criticality and Observability with Koopman Ope
rator Methods in Biological Networks\nby Enoch Yeung (UCSB) as part of
Seminar on Biological Control Systems\n\n\nAbstract\nI will present two m
ajor results to show the use of data-\ndriven Koopman methods to identify
critical states and observable\nsubspaces to solve problems in synthetic b
iology. In the first\, I\npresent the use of dynamic mode decomposition (D
MD) to model the\ntranscriptome-wide response of a root-isolate bacterium
to a novel\nchemical compound. By solving an observability maximization pr
oblem\nfor the DMD model\, we find a panel of biomarkers that can act as\n
effective biosensors for the compound\, even in field studies with the\nba
cterium. This study establishes a new precedent for reasoning about\nstate
criticality and system observability\, even without prior\nknowledge of a
network model. Second\, I present new theoretical\nresults that show how
Koopman methods can be used to evaluate\ncriticality of states to optimize
performance of a nonlinear system.\nHistorically\, this problem is solved
using either direct sensitivity\nanalysis on a known model or by generati
ng local function\ndistributions that span the nonlinear observable subspa
ce of a system.\nIn the absence of a known model\, I present a new Koopman
-based method\nfor estimating the observable subspace of a nonlinear syste
m purely\nfrom data. Our results provide a route for data-driven discovery
of\ncritical states that affect an output-based performance measure.\n\n<
b>Bio: Enoch Yeung is an Assistant Professor in the Department of Mech
anical Engineering at the University of California Santa Barbara. He is
the director of the Biological Control Laboratory\, which is an interdisc
iplinary laboratory that aims to bring together expertise in control theor
y\, synthetic biology\, and systems biology to develop new mechanisms for
biological control and computing. Prior to his appointment at UCSB\, Eno
ch was a Senior Research Scientist at the Pacific Northwest National Labor
atory. He holds a PhD in Control and Dynamical Systems from the Californi
a Institute of Technology and is the recipient of the NSF CAREER award\, t
he Army Young Investigator Program award\, and a Keck Foundation award.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/2/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Heidi Klumpe (Boston University)
DTSTART:20230926T150000Z
DTEND:20230926T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/3
DESCRIPTION:Title: Deep neural networks for predicting single cell responses and pr
obability landscapes\nby Heidi Klumpe (Boston University) as part of S
eminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/3/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Stanislav Anastassov (ETH-Zürich)
DTSTART:20230829T150000Z
DTEND:20230829T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/4
DESCRIPTION:Title: A cybergenetic framework for engineering intein-mediated integra
l feedback control systems\nby Stanislav Anastassov (ETH-Zürich) as p
art of Seminar on Biological Control Systems\n\n\nAbstract\nThe ability of
biological systems to tightly regulate targeted variables\, despite exter
nal and internal disturbances\, is known as Robust Perfect Adaptation (RPA
). Achieved frequently through biomolecular integral feedback controllers
at the cellular level\, RPA has important implications for biotechnology a
nd its various applications. In this study\, we identify inteins as a vers
atile class of genetic components suitable for implementing these controll
ers and present a systematic approach for their design. We develop a theor
etical foundation for screening intein-based RPA-achieving controllers and
a simplified approach for modeling them. We then genetically engineer and
test intein-based controllers using commonly used transcription factors i
n mammalian cells and demonstrate their exceptional adaptation properties
over a wide dynamic range. The small size\, flexibility\, and applicabilit
y of inteins across life forms allow us to create a diversity of genetic R
PA-achieving integral feedback control systems that can be used in various
applications\, including metabolic engineering and cell-based therapy.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/4/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Guillaume Gines (CNRS/ESPCI Paris)
DTSTART:20230530T150000Z
DTEND:20230530T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/5
DESCRIPTION:Title: DNA-enzyme neural networks enabling nonlinear concentration prof
ile classification\nby Guillaume Gines (CNRS/ESPCI Paris) as part of S
eminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/5/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Eszter Csibra (Imperial College)
DTSTART:20230328T150000Z
DTEND:20230328T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/6
DESCRIPTION:Title: Absolute protein quantification using fluorescence measurements
with FPCountR"\nby Eszter Csibra (Imperial College) as part of Seminar
on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/6/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Corentin Briat (ETH-Zurich)
DTSTART:20230228T160000Z
DTEND:20230228T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/7
DESCRIPTION:Title: Structural stability in integral rein control\nby Corentin B
riat (ETH-Zurich) as part of Seminar on Biological Control Systems\n\nAbst
ract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/7/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Zibo Chen (Westlake University)
DTSTART:20230131T160000Z
DTEND:20230131T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/8
DESCRIPTION:Title: A synthetic protein-level neural networks in mammalian cells
\nby Zibo Chen (Westlake University) as part of Seminar on Biological Cont
rol Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/8/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Diego Oyarzun (University of Edinburgh)
DTSTART:20221025T150000Z
DTEND:20221025T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/9
DESCRIPTION:Title: Multiobjective optimization feedback control circuits for metabo
lic engineering\nby Diego Oyarzun (University of Edinburgh) as part of
Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/9/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Fangzhou Xiao (Caltech)
DTSTART:20220927T150000Z
DTEND:20220927T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/10
DESCRIPTION:Title: Biocontrol of biomolecular systems: polyhedral constraints on b
inding's regulation of catalysis from biocircuits to metabolism\nby Fa
ngzhou Xiao (Caltech) as part of Seminar on Biological Control Systems\n\n
Abstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/10/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jean-Baptiste Lugagne (Boston University)
DTSTART:20220830T150000Z
DTEND:20220830T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/11
DESCRIPTION:Title: High-throughput single-cell control using real-time feedback\nby Jean-Baptiste Lugagne (Boston University) as part of Seminar on Biol
ogical Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/11/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Edward Hancock (University of Sydney)
DTSTART:20220726T150000Z
DTEND:20220726T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/12
DESCRIPTION:Title: Stabilization of anthitetic control via molecular buffering
\nby Edward Hancock (University of Sydney) as part of Seminar on Biologica
l Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/12/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Filo Maurice (ETH-Zurich)
DTSTART:20220628T150000Z
DTEND:20220628T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/13
DESCRIPTION:Title: A hierarchy of biomolecular proportional-integral-derivative fe
edback controllers for robust adaptation and dynamic performance\nby F
ilo Maurice (ETH-Zurich) as part of Seminar on Biological Control Systems\
n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/13/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Chelsea Hu (Caltech)
DTSTART:20220531T150000Z
DTEND:20220531T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/14
DESCRIPTION:Title: Layered feedback control overcomes performance trade-off in syn
thetic biomolecular networks\nby Chelsea Hu (Caltech) as part of Semin
ar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/14/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Michaelle N Mayalu (Stanford University)
DTSTART:20220426T150000Z
DTEND:20220426T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/15
DESCRIPTION:Title: Analysis and design of paradoxical feedback circuits for homeos
tasis of cell concentration\nby Michaelle N Mayalu (Stanford Universit
y) as part of Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/15/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Rogelio Hernandez-Lopez (UCSF)
DTSTART:20220329T150000Z
DTEND:20220329T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/16
DESCRIPTION:Title: T cell circuits that sense antigen density with an ultrasensiti
ve threshold\nby Rogelio Hernandez-Lopez (UCSF) as part of Seminar on
Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/16/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ankit Gupta (ETH-Zurich)
DTSTART:20220222T160000Z
DTEND:20220222T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/17
DESCRIPTION:Title: Frequency Spectra and the Color of Cellular Noise\nby Ankit
Gupta (ETH-Zurich) as part of Seminar on Biological Control Systems\n\nAb
stract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/17/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Christian Cuba Samaniego (UCLA)
DTSTART:20220125T160000Z
DTEND:20220125T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/18
DESCRIPTION:Title: Engineering synthetic networks for pattern recognition in mamma
lian cells\nby Christian Cuba Samaniego (UCLA) as part of Seminar on B
iological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/18/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Yitong Ma (Caltech)
DTSTART:20211217T160000Z
DTEND:20211217T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/19
DESCRIPTION:Title: Synthetic mammalian signaling circuits for robust cell populati
on contro\nby Yitong Ma (Caltech) as part of Seminar on Biological Con
trol Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/19/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ania Baetica (UCSF)
DTSTART:20211119T160000Z
DTEND:20211119T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/20
DESCRIPTION:Title: Analysis and parameter identification of four incoherent feedfo
rward loop circuit designs\nby Ania Baetica (UCSF) as part of Seminar
on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/20/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Mariana Gomez-Schiavon (National Autonomous University of Mexico)
DTSTART:20211029T150000Z
DTEND:20211029T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/21
DESCRIPTION:Title: Cora - A general approach for quantifying biological feedback c
ontrol\nby Mariana Gomez-Schiavon (National Autonomous University of M
exico) as part of Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/21/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Yili Qian (University of Wisconsin-Madison)
DTSTART:20210924T150000Z
DTEND:20210924T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/22
DESCRIPTION:Title: Decentralized control for robustness of gene networks to uninte
nded interactions\nby Yili Qian (University of Wisconsin-Madison) as p
art of Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/22/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Noah Olsman (Harvard University)
DTSTART:20210828T150000Z
DTEND:20210828T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/23
DESCRIPTION:Title: Closing the gap between theory and experiments in the design of
biomolecular feedback circuits\nby Noah Olsman (Harvard University) a
s part of Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/23/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ross Jones (University of British Columbia)
DTSTART:20210730T150000Z
DTEND:20210730T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/24
DESCRIPTION:Title: Robust and tunable signal processing in mammalian cells via eng
ineered covalent modification cycles\nby Ross Jones (University of Bri
tish Columbia) as part of Seminar on Biological Control Systems\n\nAbstrac
t: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/24/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Brayden Kell (University of Toronto)
DTSTART:20230725T150000Z
DTEND:20230725T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/25
DESCRIPTION:Title: Noise properties of adaptation-conferring biochemical control m
odules\nby Brayden Kell (University of Toronto) as part of Seminar on
Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/25/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Zachary Fox (Oak Ridge National Lab)
DTSTART:20231128T160000Z
DTEND:20231128T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/26
DESCRIPTION:Title: Single cell control using Finite State Projection based Bayesia
n Filters\nby Zachary Fox (Oak Ridge National Lab) as part of Seminar
on Biological Control Systems\n\n\nAbstract\nBiotechnology is rapidly impr
oving\, largely due to our ability to manipulate genetic material and effi
ciently measure biological processes. This talk will describe advances in
computational approaches and experimental platforms to probe and control s
tochastic biological processes within individual cells under a microscope.
I will first describe how the finite state projection approach to solving
the chemical master equation can be used to estimate the amount of protei
n in a cell given fluorescence measurements. Then\, I will show a novel pl
atform for interfacing individual cells with computational models of gene
expression using optogenetics. Chemical master equation-based Bayesian fil
ters are used to perform state estimation and control the gene expression
in each cell independently. I will also discuss how such systems could be
used to design experiments to better identify model parameters.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/26/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jakob Ruess (Inria Paris & Institut Pasteur)
DTSTART:20231219T160000Z
DTEND:20231219T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/27
DESCRIPTION:Title: From single cells to microbial consortia and back: stochastic c
hemical kinetics coupled to population dynamics\nby Jakob Ruess (Inria
Paris & Institut Pasteur) as part of Seminar on Biological Control System
s\n\n\nAbstract\nAbstract. At the single-cell level\, biochemical p
rocesses are inherently stochastic. Such processes are typically studied u
sing models based on stochastic chemical kinetics\, governed by a chemical
master equation (CME). The CME describes the time evolution of the probab
ility distribution over system states and has been a tremendously helpful
tool in shedding light on the functioning of cellular processes. However\,
single cells are not living in isolation but are part of a growing popula
tion or community. In such contexts\, stochasticity at the single-cell sca
le leads to population heterogeneity and cells may be subject to populatio
n processes\, such as selection\, that drive the population distribution a
way from the probability distribution of the single-cell process.\nHere\,
I will introduce a multi-scale modeling framework that allows one to captu
re coupled stochastic single-cell and population process. I will show that
the expected population distribution of such multi-scale models can be ca
lculated by solving a modified version of the CME that is of the same dime
nsionality as the standard CME. I will then show how such models can be us
ed to explain experimental data on plasmid copy number fluctuations and po
pulation growth in media that selects against cells that have lost the pla
smid. Finally\, I will present an optogenetic recombination system that al
lows one to partition yeast populations into different cell types via exte
rnal application of blue light to cells and show how our modeling framewor
k can be used to predict and control emerging dynamics of the population c
omposition in response to time-varying light stimuli.\n\nBio.\nJako
b Ruess received his PhD in 2015 from the Automatic Control Laboratory at
ETH Zurich\, Switzerland\, where he worked under the supervision of John L
ygeros on using moment equations of stochastic reaction networks for probl
ems such as parameter inference and experimental design. He moved on to IS
T Austria for a postdoc where he worked together with Remy Chait\, Gasper
Tkacik and Calin Guet to realize the first study on optogenetic feedback c
ontrol of gene expression dynamics inside single cells. Since 2016\, he is
a permanent researcher at the French National Institute for Research in C
omputer Science and Automation (Inria). In 2022\, he received an ERC Start
ing Grant\, entitled BridgingScales\, which aims to study the dynamics of
coupled stochastic single-cell and population processes.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/27/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Anna-Maria Makri Pistikou (TU Eindhoven)
DTSTART:20240227T160000Z
DTEND:20240227T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/28
DESCRIPTION:Title: Engineering synthetic communication in mammalian cells\nby
Anna-Maria Makri Pistikou (TU Eindhoven) as part of Seminar on Biological
Control Systems\n\n\nAbstract\nAbstract. The ability to engineer no
vel functions into mammalian cells has become a key force in biomedical re
search\, revolutionizing the field of cell diagnostics and therapeutics. I
n detail\, the rational design and implementation of synthetic\, orthogona
l mammalian sender-receiver consortia has the potential to unravel fundame
ntal design principles of cell communication circuits and offers a framewo
rk for engineering of designer cell consortia with potential applications
in cell therapeutics and artificial tissue engineering. This talk will det
ail the development of an orthogonal\, and scalable mammalian synthetic in
tercellular communication platform that exploits the programmability of sy
nthetic receptors and selective affinity and tunability of diffusing coile
d-coil (CC) peptide heterodimers\, referred to as CC-GEMS. Leveraging the
ability of CCs to exclusively bind to a selected cognate receptor\, we dem
onstrate orthogonal receptor activation\, as well as Boolean logic operati
ons at the receptor level. We show intercellular communication based on sy
nthetic CC-GEMS receptors and secreted multidomain coiled-coil (CC) ligand
s and demonstrate a minimal\, three-cell population system that can perfor
m distributed AND gate logic. Lastly\, we show CC-GEMS receptor-dependent
therapeutic protein expression. Our work provides a blueprint for the engi
neering of complex cell consortia\, with the potential to expand the aptit
ude of cell therapeutics and diagnostics.\n\nBio. Anna-Maria Makri
Pistikou earned a bachelor’s degree in nursing science from the Universi
ty of Peloponnese in 2014. She continued her studies at Maastricht Univers
ity\, where she obtained a bachelor’s degree in cell and molecular biolo
gy in 2016 and a research master’s degree in Cognitive and Clinical Neur
oscience\, specializing in Fundamental Neuroscience\, in 2018. Currently\,
she is commencing her doctoral studies in collaboration with the Institut
e of Complex Molecular Science at the Technical University of Eindhoven. H
er research interests primarily focus on the utilization of synthetic rece
ptors as tools to engineer biological structures capable of meeting human
needs.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/28/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Charlotte Bunne (ETH-Zurich & ETH AI Center)
DTSTART:20240116T160000Z
DTEND:20240116T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/29
DESCRIPTION:Title: Predicting Single-Cell Drug Responses using Optimal Transport\nby Charlotte Bunne (ETH-Zurich & ETH AI Center) as part of Seminar on
Biological Control Systems\n\n\nAbstract\nCell populations are almost alwa
ys heterogeneous in function and fate. To understand a patient’s respons
es to molecular drugs and design efficient treatments\, it is vital to rec
over the underlying population dynamics and fate decisions of single cells
upon perturbation. However\, measuring features of single cells requires
destroying them. As a result\, a cell population can only be monitored wit
h sequential snapshots\, obtained by sampling a few particles that are sac
rificed in exchange for measurements. In order to reconstruct individual c
ell fate trajectories\, as well as the overall dynamics\, one needs to re-
align these unpaired snapshots\, in order to guess for each cell what it m
ight have become at the next step.\n\nOptimal transport theory can provide
such maps\, and reconstruct these incremental changes in cell states over
time. This celebrated theory provides the mathematical link that unifies
the several contributions to model cellular dynamics that we present here:
Inference from data of an energy potential best able to describe the evol
ution of perturbation responses (Bunne et al.\, 2022a) building on the Jor
dan-Kinderlehrer-Otto (JKO) flow\; recovery of differential equations mode
ling the stochastic transitions between cell fates in developmental proces
ses (Bunne et al.\, 2022b)\; as well as zero-sum game theory models parame
terizing distribution shifts upon interventions\, which we employ to model
heterogeneous responses of tumor cells to cancer drugs (Bunne et al.\, 20
21).\n\nThis work thus provides an overview on how we can employ machine l
earning algorithms to robustly learn optimal transport models\, and how th
is enhances current drug discovery and treatment design.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/29/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Alice Boo (MIT)
DTSTART:20240326T160000Z
DTEND:20240326T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/30
DESCRIPTION:Title: Burden-Driven Multicellular Control Feedback for Microbial Cons
ortia\nby Alice Boo (MIT) as part of Seminar on Biological Control Sys
tems\n\n\nAbstract\nAbstract. Abstract:\nDivision of labor can redu
ce the burden caused by expressing large metabolic pathways. It allows to
select and design the optimal strains for enzyme expression of the pathway
of interest to improve yields and titres. However\, multicellular feedbac
k control strategies could also be an asset to improve productivity of mic
robial consortia. In this work\, we connected two E. coli strains such tha
t if one was growing faster than the other\, expression burden would slow
down growth and stabilise the growth differences between the strains. We s
howed that burden could be successfully used to balance community composit
ion. Interestingly\, our co-culture control mechanism did not reduce the f
inal product yields in either strain. Instead\, it actually enhanced them\
, improving the final yield by 81% in the slowest-growing strain and by 35
% in the fastest-growing strain\, compared to a co-culture that did not ha
ve a community control mechanism. This project provided a fundamental basi
s to explore the importance of multicellular feedback control strategies a
s mechanisms to improve the efficiency of division of labour to produce hi
gh-value compounds for metabolic engineering.\n\nBio. Alice is a po
stdoc in the Voigt Lab at MIT. Previously\, she did her PhD jointly in the
Prof Guy-Bart Stan’s Control Synthetic Biology lab and Dr Rodrigo Ledes
ma Amaro’s Synthetic Biology for Metabolic Engineering lab. She focused
on engineering multicellular feedback systems for metabolic engineering. N
ow her research focuses on building cross-kingdom multicellular systems fo
r bioremediation and environmental challenges using plants and their nativ
e root microbiome.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/30/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ying Tang (Institute of Fundamental and Frontier Sciences\, Univer
sity of Electronic Sciences and Technology of China\, Chengdu)
DTSTART:20240430T140000Z
DTEND:20240430T150000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/31
DESCRIPTION:Title: Neural-network solutions to stochastic reaction networks\nb
y Ying Tang (Institute of Fundamental and Frontier Sciences\, University o
f Electronic Sciences and Technology of China\, Chengdu) as part of Semina
r on Biological Control Systems\n\n\nAbstract\nAbstract. Machine le
arning and stochastic dynamics have deep connections and cross-feed each o
ther. As an example\, I will report our recent progress in tracking the ti
me evolution of the probability distribution for stochastic reaction netwo
rks. We propose a machine learning approach using a variational autoregres
sive network to solve the chemical master equation. We apply the approach
to examples in computational biology\, where it accurately generates the p
robability distribution over time. The results suggest a general approach
towards tracking large chemical reaction networks based on modern machine
learning.\n\nBio. Dr. Ying Tang's research interests are stochastic
dynamics\, machine learning\, and statistical physics. Since 2024\, he is
Professor at the Institute of Fundamental and Frontier Sciences\, Univers
ity of Electronic Sciences and Technology of China\, Chengdu. From 2021 to
2024\, he was an Associate researcher in Beijing Normal University\, Zhuh
ai. From 2018 to 2021\, he was a postdoctoral fellow at UCLA. He received
a PhD in physics from Shanghai Jiao Tong University in 2018 and a bachelor
degree from Zhiyuan College\, Shanghai Jiao Tong University in 2013.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/31/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Sally Wang (UMD)
DTSTART:20240528T150000Z
DTEND:20240528T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/32
DESCRIPTION:Title: Electrogenetics and Electro-biofabrication Enable Realization o
f the "Internet of Bio-Nano Things\nby Sally Wang (UMD) as part of Sem
inar on Biological Control Systems\n\n\nAbstract\nAbstract. With th
e rise of concepts like the “Internet of Things” and the advances in e
lectronic technologies\, our lives have now been occupied with smart devic
es that easily communicate with one another. These devices\, however\, lac
k the ability to freely exchange information with the world of biology\, s
ince electronics and biology possess very different communication modaliti
es. We recently introduced “electrogenetics” including an electrogenet
ic CRISPR (eCRISPR) that mediates the “conversation” between electrode
s and genetic networks by tapping into the oxyRS oxidative stress response
regulon of E. coli.\n\nIn this work\, we expanded the electrogenetic fram
ework and established a complete network of Bio-Nano Things\, which collec
tively allowed automated\, algorithm-based feedback control of electrogene
tic CRISPR activity with remote input from both a distant electronically-c
ontrolled enzyme- on-a-chip as well as a cell phone. First\, we created an
abiotic/biotic interface in order to improve information transfer between
electronics and biological systems. Inspired by nature\, using electrobio
fabrication\, we created an “artificial biofilm” that immobilized livi
ng cells on an electrode’s surface\, creating a “living electrode” b
y electrochemically assembling bacteria and thiolated polyethylene glycol
(PEG-SH) to form a thin hydrogel film. Next\, we developed an oxyRS-based
eCRISPR to more efficiently traverse the abiotic and biotic domains\, redu
ce barriers accompanying diverse biological languages\, and broaden the ba
ndwidth of electrochemical signaling\, together allowing multiplexed trans
criptional regulation on various genetic targets. These include two crucia
l quorum sensing (QS) genes that controlled the relay of electrochemical s
ignals to a broader yet selective audience of microbial populations throug
h QS communication. We then integrated the engineered interface and eCRISP
R within “BioSpark”\, a full electrogenetic system including custom-ma
de hardware and software\, for algorithm-governed automated control of gen
e expression wherein electronic inputs and optoelectronic outputs provide
for fully programmable electronic I/O. Finally\, we demonstrated a network
of Bio-Nano Things by connecting the BioSpark system with another bio-ele
ctrochemical device and human “users” to achieve remote feedback contr
ol of eCRISPR activity and more importantly\, multidirectional communicati
on between living systems regardless of physical distance. In sum\, our ne
twork enabled seamless guidance of biological processes and communities wi
th an electronic input but also the conferment and digitization of biologi
cal output to an electronic signal\, realizing an “all-connected” netw
ork of biological systems.\n\n\nBio. Sally Wang is currently a post
doc research associate at the University of Maryland\, College Park under
the guidance of Prof. William E. Bentley. She obtained her B.S. from Natio
nal Taiwan University and her Ph.D. from University of Maryland\, College
Park (Bentley Lab). Her research interests include using synthetic biology
tools to engineer communication routes between biological systems and ele
ctronics\, as well as investigating the behavior of biological systems at
the abiotic/biotic interface. She will soon begin her postdoctoral researc
h at Princeton University this summer with the Avalos lab\, using electrog
enetics to address metabolic engineering challenges in yeast systems.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/32/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Nam Tran (Drexel University)
DTSTART:20240625T150000Z
DTEND:20240625T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/33
DESCRIPTION:Title: Transfer function of network motifs and what they tell us about
signal processing in cells\nby Nam Tran (Drexel University) as part o
f Seminar on Biological Control Systems\n\n\nAbstract\nAbstract.\n\
nPart 1: Transfer function of biochemical network motifs\n\nNetwork
motifs are thought to have special signal processing functions. Biologica
l signals are often delivered in oscillations and pulses. Therefore\, it i
s useful to understand the signal processing functions of network motifs i
n response to oscillations and pulses. One tool to understand this is the
transfer function\, which allows us to view the dynamics of these motifs f
rom a frequency domain perspective. We present the transfer function for a
selection of motifs. We show how each motif exhibits different filtering
properties and highlight their potential roles in signaling within the cel
l.\n\nPart 2: Sensitivity function of biochemical feedback loops\n\
nFeedback loops allow biological systems to effectively respond to their c
hanging environment. However\, the biochemical conditions that make up the
se feedback loop mechanisms can vary. Quantifying how robust these feedbac
k loops are to such variations can help us understand how well biological
systems implement feedback. Previous research has found that cells might c
ommonly use negative feedback because it allocates the sensitivity to para
meters that are unlikely to vary such as cooperative binding\, while remai
ning insensitive to parameters such as production and degradation rates. I
n this research\, we performed sensitivity analysis on feedback loops cons
isting of one and two species involving combinations of positive and negat
ive feedback. Our analysis can provide insight into how synthetic biologic
al circuits can be reliably designed and used in changing environments. \n
\n\nBio. Nam is currently a postdoc at Drexel University under Prof
. Ania-Ariadna Baetica. He obtained his B.S. at the University of Melbourn
e (Australia) and PhD at Swinburne University (Australia). His current res
earch interests include studying robustness of biological feedback loops\,
and ways to generalise this for arbitrary dynamics and feedback architect
ures. Nam enjoys talking about control theory and dynamical systems and ph
ysical models in biology\, so please don't be shy to reach out if you want
to chat!\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/33/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Kirill Sechkar (University of Oxford)
DTSTART:20240730T150000Z
DTEND:20240730T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/34
DESCRIPTION:Title: Modelling for resource-aware analysis and design of synthetic g
ene circuits in bacteria\nby Kirill Sechkar (University of Oxford) as
part of Seminar on Biological Control Systems\n\n\nAbstract\nSynthetic gen
es compete for resources among themselves and with the host cell's native
genes\, burdening the host and impeding its growth. These resource couplin
gs\, exhibited by a wide range of biological processes\, can give rise to
unexpected behaviours and impair biotechnologies' predictability\, modular
ity\, efficiency\, and functional lifespan. \n\nIn this talk\, I will prov
ide an overview of our work on using mathematical modelling to understand
and forecast resource competition phenomena\, as well as to mitigate their
unwanted effects on synthetic gene circuit performance in bacteria. First
\, we describe our recently published resource-aware bacterial cell model\
, developed to realistically capture competition for ribosomes whilst main
taining maximum ease of gene circuit design and analysis. This model is th
en used to propose and examine the performance of a novel versatile biomol
ecular controller aimed at preventing the loss of engineered functionaliti
es by engineered cell populations. Second\, we showcase how resource-aware
modelling of RNA-based circuits can help to elucidate their behaviour and
explain unexpected experimental outcomes.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/34/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Ted Grunberg (MIT)
DTSTART:20240827T150000Z
DTEND:20240827T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/35
DESCRIPTION:Title: Error bounds for the linear noise approximation to stationary d
istributions of chemical reaction networks\nby Ted Grunberg (MIT) as p
art of Seminar on Biological Control Systems\n\n\nAbstract\nBiomolecules i
nteracting according to a chemical reaction network are often modeled by a
continuous time Markov chain that describes the evolution of counts of th
e biomolecules over time. Such Markov chains typically have a large or inf
inite number of states and are thus computationally difficult to analyze.
Therefore\, approximations exploiting the fact that the volume and molecul
ar counts are both large are often used. The most common such approximatio
ns are the reaction rate equations (RREs)\, which are a deterministic mode
l\, and the linear noise approximation (LNA)\, which is a diffusion approx
imation to fluctuations about the solution of the RREs. Limit theorem resu
lts\, due to Kurtz (1971)\, establish the validity of the RREs and of the
LNA for finite times. However\, such results do not justify approximating
the stationary distribution of a chemical reaction network using the RREs
or LNA. The validity of these approximations for the stationary distributi
on has only been investigated for special cases\, such as when the Markov
chain’s state space is bounded in concentration\, or when the chemical r
eaction network has a special structure. Here\, we use Stein’s method to
derive bounds on the approximation error for the LNA applied to the stati
onary distribution of a chemical reaction network. Specifically\, we give
a non-asymptotic bound on the 1-Wasserstein distance between an appropriat
ely scaled Markov chain and its LNA\, under certain technical conditions\,
that decays to zero with increasing system size. We further show how glob
al stability properties of an equilibrium point of the RREs are sufficient
to obtain such error bounds. Our results can be used to check when the LN
A is a suitable approximation of the stationary distribution of a chemical
reaction network without having to perform computationally costly simulat
ions.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/35/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Davide Salzano
DTSTART:20240924T150000Z
DTEND:20240924T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/36
DESCRIPTION:Title: In-vivo distributed multicellular control of gene expression in
synthetic microbial consortia\nby Davide Salzano as part of Seminar o
n Biological Control Systems\n\n\nAbstract\nCybergenetics is an emerging d
iscipline at the interface between synthetic biology and control engineeri
ng\, aimed at exploiting feedback control to engineer reliable and robust
synthetic biological circuits to regulate and dynamically tune the express
ion of a target gene in the host organism. Both E.coli and mammalian cells
have been engineered so as to realize feedback control loops that regulat
e gene expression intracellularly (a strategy known as embedded control).
However\, embedded controllers have several limitations\, including modula
rity\, as any change in the controller design requires a complete re-engin
eering of the designed gene network.\nA solution to overcome these problem
s is to distribute the required functionalities to different populations s
uch that each of them carries out a specific task. This control paradigm\,
known as multicellular control\, relies on engineering a Controller popul
ation that senses and computes a control action used to regulate in real-t
ime the state of a process hosted in a second population\, denoted as Targ
ets. In this talk I will present a possible biological implementation and
experimental validation of Controllers and Targets in E.coli. Specifically
\, the response of both populations has been characterized\, showing that
they can establish effective communication between each other and influenc
e their behaviour so the Targets can achieve the desired behaviour decided
by the controllers. Additionally\, I will show clear evidence that the ar
chitecture allows for tunable regulation of a desired gene in the Targets\
, and that such regulation is robust to perturbations such as imbalances b
etween the size of the two populations. The developed architecture can ena
ble the realisation of robust modules with potential application in biomed
icine and industrial bioproduction.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/36/
END:VEVENT
BEGIN:VEVENT
SUMMARY:María Cristina Cannarsa (Sapienza Università di Roma)
DTSTART:20241029T150000Z
DTEND:20241029T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/37
DESCRIPTION:Title: Light-driven synchronization of optogenetic clocks\nby Mar
ía Cristina Cannarsa (Sapienza Università di Roma) as part of Seminar on
Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/37/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Fengjie Zhao (USC)
DTSTART:20241210T160000Z
DTEND:20241210T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/38
DESCRIPTION:Title: Control of extracellular electron transfer in phylogenetically
diverse electroactive bacteria\nby Fengjie Zhao (USC) as part of Semin
ar on Biological Control Systems\n\n\nAbstract\nExtracellular electron tra
nsfer (EET) is a process that allows electroactive bacteria to route elect
rons from the cellular interior to external electron acceptors under anaer
obic conditions. Shewanella oneidensis MR-1\, which can respire external m
inerals\, is a model electroactive microorganism and utilizes a network of
multiheme c-type cytochromes for EET. In addition\, S. oneidensis MR-1 is
able to form living conductive biofilms for long-distance electron transp
ort. Here\, we introduced optogenetic circuits into S. oneidensis to contr
ol electron transfer at different scales. We first developed a lithographi
c strategy to pattern the conductive biofilms of S. oneidensis on electrod
es by a blue light-induced genetic circuit\, which allowed us to demonstra
te tunable conduction of living biofilms dependent on pattern geometry. Ne
xt\, we developed a red light-induced genetic circuit in S. oneidensis bas
ed on a reported iLight system. This red light-induced genetic circuit was
used to control cytochrome expression and EET activity in S. oneidensis w
ith light. Beyond environmental mineral-respiring bacteria\, recent studie
s have also suggested that some microbes in the human gut are capable of E
ET through a flavin-based EET mechanism\, despite being flavin auxotrophs.
To broaden and deepen our understanding of EET in the gut microbial commu
nity\, we performed electrochemical measurements on co-cultures of Enteroc
occus faecalis OG1RF and Escherichia coli MG1655. The results showed that
E. faecalis used flavins that are secreted by E. coli as electron shuttles
to mediate EET. Our studies reveal a synergistic mechanism that modulates
EET activity in the gut microbial community.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/38/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Gennady Gorin (Caltech)
DTSTART:20231107T160000Z
DTEND:20231107T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/39
DESCRIPTION:Title: Stochastic foundations for single-cell RNA sequencing\nby G
ennady Gorin (Caltech) as part of Seminar on Biological Control Systems\n\
n\nAbstract\nSingle-cell RNA sequencing\, which quantifies cell transcript
omes\, has seen widespread adoption\, accompanied by a proliferation of an
alytic methods. However\, there has been relatively little systematic inve
stigation of its best practices and their underlying assumptions\, leading
to challenges and discrepancies in analysis. I motivate a set of generic\
, principled strategies for modeling the biological and technical stochast
icity in sequencing experiments\, and use case studies to illustrate their
prospects for the discovery and interpretation of biophysical kinetics.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/39/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Giuliano De Carluccio (MIT)
DTSTART:20240206T160000Z
DTEND:20240206T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/40
DESCRIPTION:Title: The CASwitch: a synthetic biology solution for high-performance
inducible gene expression systems in biotechnology\nby Giuliano De Ca
rluccio (MIT) as part of Seminar on Biological Control Systems\n\n\nAbstra
ct\nAbstract. Achieving tight and reliable control of gene expressi
on in living cells is crucial for the practical application of synthetic b
iology. While transcriptional-based inducible gene systems are widely used
in synthetic biology\, they often suffer from shortcomings\, including un
intended background gene expression (leakiness). Traditional approaches to
enhance these systems involves iterative screening of transcription facto
r and promoter libraries\, facing challenges in finding the right balance
between leakiness and maximal induced expression\, and being ad-hoc soluti
ons.\n\nIn this seminar\, I will discuss how control theory\, coupled with
a quantitative synthetic biology approach\, offers a general solution to
enhance the performance of transcriptional-based inducible gene systems wi
thout modifying the transcription factor (TF) or its promoter. I will show
how a combination of Coherent Feed-Forward Loop (CFFL) and Mutual Inhibit
ion (MI) network motifs\, biologically implemented through a CasRx endorib
onuclease\, results in the development of a mammalian synthetic gene circu
it achieving quasi-zero leakiness while maintaining high levels of express
ion\; that we named CASwitch. Finally\, I will showcase the versatility of
the CASwitch through three different applications\, including enhancing t
he sensitivity of a whole-cell biosensor\, regulating the expression of a
toxic gene\, and facilitating the inducible production of Adeno-Associated
Virus (AAV) vectors.\n\nThis talk offers insights into the design of synt
hetic gene circuits as a means to improve existing inducible gene expressi
on systems\, providing tight and reliable control over gene expression for
real-world applications.\n\nBio. Giuliano De Carluccio is a Postd
octoral Researcher in the Collins Lab at MIT\, working on the development
of RNA-based devices to control gene expression in the field of mRNA thera
peutics. He earned his Ph.D. in Industrial Bioengineering in 2023 from the
University of Naples Federico II. During his PhD studies\, he worked with
Diego di Bernardo at the Telethon Institute of Genetic and Medicine in Na
ples\, employing quantitative synthetic biology and mathematical modeling
to design a new gene expression control system in mammalian cells for real
-world applications.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/40/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Massimo Bellato (University of Padova)
DTSTART:20250128T160000Z
DTEND:20250128T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/41
DESCRIPTION:Title: From bacterial communication to tackle Antimicrobial Resistance
(AMR)\nby Massimo Bellato (University of Padova) as part of Seminar o
n Biological Control Systems\n\n\nAbstract\nThe increasing resistance of b
acteria to antimicrobials poses a significant challenge for public health.
However\, while the pursuit of new antimicrobial agents is often outpaced
by the rapid development of bacterial resistance\, synthetic biology can
offer innovative tools to combat this issue. This seminar will explore an
ongoing project that starting from a systems biology approach to investiga
te the properties of bacterial communication equilibrium\, has has led to
the investigation of complementary strategies to disrupt AMR-associated me
chanisms\, including (i) the degradation of external signaling molecules\,
(ii) CRISPR interference in pathogenic organisms\, and (iii) delivery sys
tems designed to transfer therapeutic genetic circuits into target cells.\
n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/41/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Takehiro Tottori (RIKEN)
DTSTART:20250225T140000Z
DTEND:20250225T150000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/42
DESCRIPTION:Title: Theory for Optimal Estimation and Control under Resource Limita
tions and Its Applications to Biological Information Processing and Decisi
on-Making\nby Takehiro Tottori (RIKEN) as part of Seminar on Biologica
l Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/42/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Josiah Passmore (Utrecht University)
DTSTART:20250325T150000Z
DTEND:20250325T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/43
DESCRIPTION:Title: Outcome-Driven Microscopy: Closed-Loop Optogenetic Control of
Cell Biology\nby Josiah Passmore (Utrecht University) as part of Semi
nar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/43/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Sebastian Castillo-Hair (University of Washington)
DTSTART:20250429T150000Z
DTEND:20250429T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/44
DESCRIPTION:Title: Generalizable design of human tissue\, cell type\, and cell sta
te-specific gene expression via deep learning models of genomic accessibi
lity\nby Sebastian Castillo-Hair (University of Washington) as part of
Seminar on Biological Control Systems\n\n\nAbstract\nCells across tissues
\, developmental stages\, and disease conditions adopt distinct \nintracel
lular states – epigenomic\, transcriptomic\, and proteomic profiles –
to \ncompartmentalize function in time and space. The ability to write DNA
- and RNA-\nencoded programs that sense and interface with cellular states
has transformative \npotential for biotechnology\, for example in develop
ing gene therapies with tissue\, \ncell type\, and disease-specificity to
minimize off-target effects\, and in guiding stem \ncells towards differen
tiated cell states for regenerative medicine. However\, our \nlimited unde
rstanding of how basic cellular processes\, such as gene expression\, \nar
e regulated in different cellular states hinders any attempt at rationally
\ndesigning such genetic programs. Neural network (NN) and generative mod
els \nthat capture different aspects of cell state regulation from large o
mics datasets \noffer a powerful tool to overcome these barriers.\n\nHere\
, we present our recent work on programming cell type- and state-specific
\ngene expression via synthetic enhancers – short DNA elements that regu
late \ntranscription. We trained NN models on genomic accessibility data\,
based on the \nrationale that active enhancers reside in genomic regions
with an open\, accessible \nchromatin state. These data are available for
hundreds of human cell types and \ntissues and thus offer a vast resource
for enhancer design. Using data of >3 million\nDNase-hypersensitive sites
across 733 cell types and tissues\, we trained NN \nmodels to predict acce
ssibility from sequence and used them to design de novo \nsequences with c
ell type-specific accessibility. To validate our designs\, we tested a \nl
ibrary of 9\,000 synthetic enhancers in a panel of 10 human cell lines –
including \nHepG2 (liver)\, K562 (lymphoid)\, SJCRH30 (muscle)\, WERI-Rb1
(retina)\, and MCF7 \n(breast) – as well as in vivo in mouse retinas. I
n most cases\, synthetic sequences \nshowed significantly higher enhancer
activity and specificity in their target cells \ncompared to control genom
ic enhancers. Our results demonstrate that NN models \nof genomic accessib
ility can be used to program gene expression specific to a large\nvariety
of cell types\, highlighting the potential of NN-driven design for synthet
ic \nbiology.\n\nBio. Sebastian is a postdoctoral scholar at the EC
E Department\, working in Georg Seelig’s lab. Sebastian’s research foc
uses on synthetic biology\, specifically on using high-throughput assays a
nd deep learning methods to understand how untranslated mRNA sequences reg
ulate translation and stability in human cells\, and to engineer improved
sequences for therapeutics applications. Before\, Sebastian earned his Ph.
D. in Bioengineering at Rice University\, where he worked on optogenetics
and bacterial synthetic biology.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/44/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Maren Philipps (e Friedrich-Wilhelms-Universität Bonn\, Bonn\, Ge
rmany)
DTSTART:20250527T150000Z
DTEND:20250527T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/45
DESCRIPTION:Title: Universal differential equations for systems biology: Current s
tate and open problems\nby Maren Philipps (e Friedrich-Wilhelms-Univer
sität Bonn\, Bonn\, Germany) as part of Seminar on Biological Control Sys
tems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/45/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Eric De Giuli (University of Toronto)
DTSTART:20250624T150000Z
DTEND:20250624T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/46
DESCRIPTION:Title: Noise equals endogenous control\nby Eric De Giuli (Universi
ty of Toronto) as part of Seminar on Biological Control Systems\n\n\nAbstr
act\nStochastic systems have a control-theoretic interpretation in which n
oise plays the role of endogenous control. In the weak-noise limit\, relev
ant at low temperatures or in large populations\, control is optimal and a
n exact mathematical mapping from noise to control can be drawn. I will ex
plain this mapping in simple language and argue that it is particularly re
levant for multistable chemical reaction networks\, where it can build int
uition for why biological mechanisms can work better in the presence of no
ise\; and how agentic behavior emerges naturally without recourse to mysti
cism.\n\nBio: Eric De Giuli obtained his Hon.BSc with High Distinct
ion in Mathematics and Physics from the University of Toronto in 2006. At
UBC\, he obtained a MSc in Geophysics (2009) and a Ph.D. in Applied Mathem
atics (2013)\, on turbulence\, and granular matter\, respectively. As a po
stdoctoral fellow in Matthieu Wyart's group at NYU and then EPFL\, he work
ed on the theory of amorphous solids. From 2017-2019 he was Junior Researc
h Associate at the Institut Philippe Meyer\, École Normale Supérieure\
, Paris\, where he branched out to apply the tools of disordered systems p
hysics to other complex systems. In 2019 he returned to Canada as Assistan
t Professor (2019-2024) and now Associate Professor (2025-) of Complexity
Physics at Toronto Metropolitan University. His group is now focused on ph
ysics models of language and theory for chemical reaction networks\, with
applications to biology.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/46/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Daniel Eaton (Harvard Medical School)
DTSTART:20250729T150000Z
DTEND:20250729T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/47
DESCRIPTION:Title: Essentialome-Wide Multigenerational Imaging Reveals Mechanistic
Origins of Cell Growth Laws\nby Daniel Eaton (Harvard Medical School)
as part of Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/47/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Frank Britto Bisso (Carnegie Mellon University)
DTSTART:20250826T150000Z
DTEND:20250826T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/48
DESCRIPTION:Title: Programming genetic circuits that operate as neural networks\nby Frank Britto Bisso (Carnegie Mellon University) as part of Seminar o
n Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/48/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Eugenio Cinquemani (INRIA Grenoble)
DTSTART:20250930T150000Z
DTEND:20250930T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/49
DESCRIPTION:Title: Single-cell data reveal heterogeneity of investment in ribosome
s across a bacterial population\nby Eugenio Cinquemani (INRIA Grenoble
) as part of Seminar on Biological Control Systems\n\n\nAbstract\nIn this
seminar I will present our recently published work (Pavlou et al. Nat Comm
un 16\, 285\, 2025)\, described next.\nRibosomes are responsible for the s
ynthesis of proteins\, the major component of cellular biomass. Classical
experiments have established a linear relationship between the fraction of
resources invested in ribosomal proteins and the rate of balanced growth
of a microbial population. Very little is known\, however\, about how the
investment in ribosomes varies over individual cells in a population. We t
herefore extended the study of ribosomal resource allocation from populati
ons to single cells\, using a combination of time-lapse fluorescence micr
oscopy and statistical inference. We found a large variability of ribosome
concentrations and growth rates in conditions of balanced growth of the m
odel bacterium Escherichia coli in a given medium\, which cannot be accoun
ted for by the population-level growth law. A large variability in the all
ocation of resources to ribosomes was also found during the transition of
the bacteria from a poor to a rich growth medium. While some cells immedia
tely adapt their ribosome synthesis rate to the new environment\, others d
o so only gradually. Our results thus reveal a range of strategies for inv
esting resources in the molecular machines at the heart of cellular self-r
eplication. This raises the fundamental question whether the observed vari
ability is an intrinsic consequence of the stochastic nature of the underl
ying biochemical processes or whether it improves the fitness of Escheric
hia coli in its natural environment.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/49/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Tuan Pham (University of Amsterdam)
DTSTART:20251028T150000Z
DTEND:20251028T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/50
DESCRIPTION:Title: Adaptation under Dynamic Genotype-Phenotype Map as Out-of-Equil
ibrium Learning\nby Tuan Pham (University of Amsterdam) as part of Sem
inar on Biological Control Systems\n\n\nAbstract\nGenetic and neural netwo
rks are adaptive - they change slowly in response to the collective states
of their constituting elements – genes or neurons. For genotypes encode
d by such networks\, adaptation to environmental variations emerges from t
he requirement to reach a predetermined optimal phenotype. By establishing
a mathematical correspondence between this stochastic optimisation proces
s and a non-equilibrium learning rule for its connections\, we show how a
random gene regulatory network self-organises into a robust structure with
in an intermediate level of external noise.\n\nBio. Tuan Pham is a
fellow at the Dutch Institute for Emergent Phenomena and the Institute for
Theoretical Physics\, University of Amsterdam. His work focuses on applic
ations of non-equilibrium statistical physics to complex systems with mult
iple timescales\, including biological adaptation\, social dynamics and ne
ural networks.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/50/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jordi Pla Mauri (CSIC/UPF)
DTSTART:20260127T160000Z
DTEND:20260127T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/51
DESCRIPTION:Title: Beyond Reaction: Minimal Genetic Circuits for Cellular Anticipa
tion\nby Jordi Pla Mauri (CSIC/UPF) as part of Seminar on Biological C
ontrol Systems\n\n\nAbstract\nAbstract: Living systems anticipate future c
onditions to reduce environmental uncertainty—a form of active adaptatio
n found in both neural and non-neural agents. In this talk\, I present min
imal genetic circuits inspired by the Moving Average Convergence Divergenc
e principle from finance. By leveraging this simple principle\, these circ
uits enable cells to predict environmental trends rather than merely react
ing to changes.\n\nThrough mathematical modeling\, we show that these synt
hetic circuits generate robust anticipatory responses across diverse condi
tions. These results suggest that simple\, evolvable circuits can support
biological prediction\, providing a foundation for engineering sophisticat
ed predictive behaviors in living systems.\n\nBio: Jordi Pla-Mauri is a Ph
D candidate at the ICREA–Complex Systems Lab\, Universitat Pompeu Fabra.
His research leverages synthetic biology to explore distributed computati
on in cell consortia\, criticality in living systems\, and the implementat
ion of learning motifs and basal cognition in single cells.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/51/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Armin Mohammadie Zand (ETH-Zurich)
DTSTART:20260428T150000Z
DTEND:20260428T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/52
DESCRIPTION:by Armin Mohammadie Zand (ETH-Zurich) as part of Seminar on Bi
ological Control Systems\n\nInteractive livestream: https://mit.zoom.us/j/
94325327926?pwd=TTBMSXlhT2xJT1lzcEM3WTZmTFpBQT09\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/52/
URL:https://mit.zoom.us/j/94325327926?pwd=TTBMSXlhT2xJT1lzcEM3WTZmTFpBQT09
END:VEVENT
BEGIN:VEVENT
SUMMARY:Dongju Lim & Seokhwan Moon (KAIST)
DTSTART:20260224T160000Z
DTEND:20260224T170000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/53
DESCRIPTION:Title: Toward Single-Cell Control: Noise-Robust Perfect Adaptation in
Biomolecular Systems\nby Dongju Lim & Seokhwan Moon (KAIST) as part of
Seminar on Biological Control Systems\n\nAbstract: TBA\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/53/
END:VEVENT
BEGIN:VEVENT
SUMMARY:Jake McGrath (UT Austin)
DTSTART:20260331T150000Z
DTEND:20260331T160000Z
DTSTAMP:20260404T111217Z
UID:Biocontrol/54
DESCRIPTION:Title: Using control theory to study biology: a case study on muscle f
unction and evolution\nby Jake McGrath (UT Austin) as part of Seminar
on Biological Control Systems\n\n\nAbstract\nBiological systems exhibit a
remarkable range of dynamical behaviors --- spanning development and repai
r\, regulation\, sensing and signaling\, motor control\, and adaptation. P
owered by the transduction of stored energy\, these processes enable organ
isms to achieve functional goals while maintaining stability far from ther
modynamic equilibrium. Such dynamics span vast scales in space and time\,
from nanometer-scale molecular motors driving cellular processes to organi
sm-level motion\, and from millisecond reflexes to evolutionary adaptation
across generations.\nWhile physical laws constrain these dynamics\, they
do not fully explain how living systems sense\, decide\, and regulate thei
r behavior. In this talk\, I present control theory as a unifying framewor
k for understanding how biological systems achieve robust\, goal-directed
dynamics across spatiotemporal scales. I focus on muscle and actin–myosi
n systems as a model platform\, using a control-theoretic lens to explore
how muscle-like behavior can inform robotic design\, how nonlinearities sh
ape performance tradeoffs\, and how such nonlinearities may arise through
biological evolution.\n
LOCATION:https://stable.researchseminars.org/talk/Biocontrol/54/
END:VEVENT
END:VCALENDAR