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Publications of Lingchong You    :chronological  alphabetical  combined listing:

%% Papers Published   
@booklet{Tanouchi08,
   Author = {Y. Tanouchi and D. Tu and J. Kim and L. You},
   Title = {Noise Reduction by Diffusional Dissipation in a Minimal
             Quorum Sensing Motif},
   Journal = {Plos Computational Biology},
   Volume = {4},
   Number = {8},
   Year = {2008},
   Month = {August},
   ISSN = {1553-734X},
   Abstract = {Cellular interactions are subject to random fluctuations
             (noise) in quantities of interacting molecules. Noise
             presents a major challenge for the robust function of
             natural and engineered cellular networks. Past studies have
             analyzed how noise is regulated at the intracellular level.
             Cell-cell communication, however, may provide a
             complementary strategy to achieve robust gene expression by
             enabling the coupling of a cell with its environment and
             other cells. To gain insight into this issue, we have
             examined noise regulation by quorum sensing (QS), a
             mechanism by which many bacteria communicate through
             production and sensing of small diffusible signals. Using a
             stochastic model, we analyze a minimal QS motif in
             Gram-negative bacteria. Our analysis shows that diffusion of
             the QS signal, together with fast turnover of its
             transcriptional regulator, attenuates low-frequency
             components of extrinsic noise. We term this unique mechanism
             "diffusional dissipation'' to emphasize the importance of
             fast signal turnover (or dissipation) by diffusion. We
             further show that this noise attenuation is a property of a
             more generic regulatory motif, of which QS is an
             implementation. Our results suggest that, in a QS system, an
             unstable transcriptional regulator may be favored for
             regulating expression of costly proteins that generate
             public goods.},
   Key = {Tanouchi08}
}

@booklet{You06,
   Author = {L. You and J. Yin},
   Title = {Evolutionary design on a budget: robustness and optimality
             of bacteriophage T7},
   Journal = {Iee Proceedings Systems Biology},
   Volume = {153},
   Number = {2},
   Pages = {46 -- 52},
   Year = {2006},
   Month = {March},
   ISSN = {1741-2471},
   Abstract = {Exploring how biological systems have been 'designed' by
             evolution to achieve robust behaviours is now a subject of
             increasing research effort. Yet, it still remains unclear
             how environmental factors may contribute to this process.
             This issue is addressed by employing a detailed computer
             model for the intracellular growth of phage T7. More than
             150 000 in silico T7 mutants were generated and the rates
             and efficiencies of their growth in two host environments,
             namely, a realistic environment that offered finite host
             resources for the synthesis of phage functions and a
             hypothetical environment where the phage Was Supplied
             infinite host resources, were evaluated. Results revealed
             two key properties of phage T7. First, T7 growth was overall
             robust with respect to perturbations in its parameters, but
             fragile with respect to changes in the ordering of its
             genetic elements. Secondly, the wild-type T7 had close to
             optimal fitness in the finite environment. Furthermore, a
             strong correlation was found between fitness and growth
             efficiency in the finite environment. The results underscore
             the potential importance of the environment in shaping
             robust design of a biological system. In particular, the
             strong correlation between fitness and growth efficiency
             suggests that T7 may have evolved to maximise its growth
             rate by minimising waste of finite resources.},
   Key = {You06}
}

@booklet{Srivastava02,
   Author = {R. Srivastava and L. You and J. Summers and J.
             Yin},
   Title = {Stochastic vs. deterministic modeling of intracellular viral
             kinetics},
   Journal = {Journal Of Theoretical Biology},
   Volume = {218},
   Number = {3},
   Pages = {309 -- 321},
   Year = {2002},
   Month = {October},
   ISSN = {0022-5193},
   Abstract = {Within its host cell, a complex coupling of transcription,
             translation, genome replication, assembly, and virus release
             processes determines the growth rate of a virus.
             Mathematical models that account for these processes can
             provide insights into the understanding as to how the
             overall growth cycle depends on its constituent reactions.
             Deterministic models based on ordinary differential
             equations can capture essential relationships among virus
             constituents. However, an infection may be initiated by a
             single virus particle that delivers its genome, a single
             molecule of DNA or RNA, to its host cell. Under such
             conditions, a stochastic model that allows for inherent
             fluctuations in the levels of viral constituents may yield
             qualitatively different behavior. To compare modeling
             approaches, we developed a simple model of the intracellular
             kinetics of a generic virus, which could be implemented
             deterministically or stochastically. The model accounted for
             reactions that synthesized and depleted viral nucleic acids
             and structural proteins. Linear stability analysis of the
             deterministic model showed the existence of two nodes, one
             stable and one unstable. Individual stochastic simulation
             runs could access and remain at the unstable node. In
             addition, deterministic and averaged stochastic simulations
             yielded different transient kinetics and different
             steady-state levels of viral components, particularly for
             low multiplicities of infection (MOI), where few virus
             particles initiate the infection. Furthermore, a bimodal
             population distribution of viral components was observed for
             low MOI stochastic simulations. The existence of a low-level
             infected subpopulation of cells, which could act as a viral
             reservoir, suggested a potential mechanism of viral
             persistence. (C) 2002 Elsevier Science Ltd. All rights
             reserved.},
   Key = {Srivastava02}
}

@booklet{Endy99,
   Author = {D. Endy and L. You and I. J. Molineux and J.
             Yin},
   Title = {Prediction, design, and characterization of alternate
             genetic element orders for bacteriophage
             T7.},
   Journal = {Abstracts Of Papers Of The American Chemical
             Society},
   Volume = {217},
   Pages = {U205 -- U205},
   Year = {1999},
   Month = {March},
   ISSN = {0065-7727},
   Key = {Endy99}
}

@booklet{You96,
   Author = {L. You and F. H. Arnold},
   Title = {Directed evolution of subtilisin E in Bacillus subtilis to
             enhance total activity in aqueous dimethylformamide},
   Journal = {Protein Engineering},
   Volume = {9},
   Number = {1},
   Pages = {77 -- 83},
   Year = {1996},
   Month = {January},
   ISSN = {0269-2139},
   Abstract = {Sequential rounds of error-prone PCR to introduce random
             mutations and screening of the resultant mutant libraries
             have been used to enhance the total catalytic activity of
             subtilisin E significantly in a non-natural environment,
             aqueous dimethylformamide (DMF). Seven DNA substitutions
             coding for three new amino acid substitutions were
             identified in a mutant isolated after two additional
             generations of directed evolution carried out on 10M
             subtilisin E, previously 'evolved' to increase its specific
             activity in DMF. A Bacillus subtilis-Escherichia coli
             shuttle vector was developed in order to increase the size
             of the mutant library that could be established in
             B.subtilis and the stringency of the screening process was
             increased to reflect total as well as specific activity.
             This directed evolution approach has been extremely
             effective for improving enzyme activity in a non-natural
             environment: the resulting-evolved 13M subtilisin exhibits
             specific catalytic efficiency towards the hydrolysis of a
             peptide substrate succinyl-Ala-Ala-Pro-Phe-p-nitroanilide in
             60\% DMF solution that is three times that of the parent 10M
             and 471 times that of wild type subtilisin E. The total
             activity of the 13M culture supernatant is enhanced 16-fold
             over that of the parent 10M.},
   Key = {You96}
}


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