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\begin{document}

\title{ITQB Preprint Journal Club: 3 July 2018}



\author[1]{Ambre Jousselin}%
\author[1]{m.n.melo}%
\author[1]{Zach Hensel}%
\affil[1]{ITQB NOVA Preprint Journal Club}%


\vspace{-1em}



  
  \date{May 29, 2024}


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\selectlanguage{english}
\begin{abstract}
This is a review of the preprint "Cell boundary confinement sets the
size and position of the~\emph{E. coli} chromosome" by~Fabai Wu, Pinaki
Swain, Louis Kuijpers, Xuan Zheng, Kevin Felter, Margot Guurink,
Debasish Chaudhuri, Bela Mulder and Cees Dekker. The article was posted
on bioRxiv on 15 June 2018 (\url{https://doi.org/10.1101/348052}). The
ITQB Preprint Journal club reviewed the article on 3 July 2018. This
review was written by Dr. Ambre Jousselin, who led the Preprint Journal
Club. Dr. Manuel Melo made major contributions to analysis of
simulations, and Dr. Zach Hensel helped edit the review for posting on
PREreview and commented on microscopy methods.%
\end{abstract}%



\sloppy


\section*{\texorpdfstring{Cell boundary confinement sets the size and
position of the~\emph{E. coli}
chromosome}{Cell boundary confinement sets the size and position of the~E. coli chromosome}}

{\label{130373}}

\subsection*{Fabai Wu, Pinaki Swain, Louis Kuijpers, Xuan Zheng, Kevin
Felter, Margot Guurink, Debasish Chaudhuri, Bela Mulder, Cees
Dekker}

{\label{328439}}

\textbf{bioRxiv 348052} doi: \url{https://doi.org/10.1101/348052}

\subsection*{Overview}

{\label{656282}}

Wu et al. are demonstrating the importance of longitudinal confinement
to determine the size and the position of the chromosome in \emph{E.
coli}.

\par\null

Variations of cell sizes, from short cells to long non dividing cells
were obtained through genetic manipulations. Fluorescence imaging
reveals compaction or expansion of the nucleoid size in relation with
cell length. SIM images show a dynamic structural organization of the
chromosome whereas the nucleoid exhibits a very accurate position at
mid-cell. The authors are using a coarse grained simulation that fits
the observed experimental data and propose that molecular crowding are
determinant for chromosome organization.

\par\null

\subsection*{Feedback}

{\label{383478}}

The article was chosen among recent bioRxiv papers to be discussed in
our ITQB preprint journal club. People appreciated the elegant systems
used by the authors to reach very long and very short~\emph{E. coli}
cells and generally agree with the interpretation of the experimental
data. Molecular dynamics simulations were debated because of some
uncertainty about how crowders were added.

\par\null

Most importantly, this paper raised new questions that could be
interesting for future work:

\begin{itemize}
\tightlist
\item
  What would happen to the chromosome size, position and organization in
  a cell that does not have cell wall (L-form) or has a different shape?
\item
  To observe in vivo the effect of the crowders, it was suggested to
  play with the osmolarity of the medium. The increase in crowder
  concentration could be investigated by a FRET sensor like the ones
  developed by Boersma et al.
  ---~\url{https://doi.org/10.1038/nmeth.3257} --- Since we expect
  crowders to be mostly rRNA and tRNA, RplA fusion should help to
  visualize the potential localization of crowders in long cells.
\end{itemize}

\subsection*{Major concerns}

{\label{339209}}

\subsubsection*{Regarding the nucleoid
visualization}

{\label{419130}}

Figure 1: It was not completely clear for us why nucleoid HU-mYPet is
constant. The signal is diluted because of the nucleoid length, but
should not we expect some change in the number of HU-mYPet molecules
bound to the chromosome, because of (1) a change in HU-mYPet
concentration in the perturbed growth conditions, or (2) changes in
local DNA structure that influence specific or non-specific binding?
Given how interesting it is that the total number of bound HU-mYPet
stays constant, we would like to see a more complete description of how
this was calculated. Particularly: how was background estimated and
subtracted?

\par\null

We find the assignment of a helix to the observations in Fig. S3B to be
somewhat unfounded, and also that this is not an actual prediction of
the model: in the model there is much more implicit DNA besides the
backbone. Fig. 1 of the Chaudhuri 2012 PRL paper shows that even though
the backbone arranges as a helix overall DNA distribution is expected to
be more uniform.

\subsubsection*{}

{\label{112264}}

\subsubsection*{Regarding imaging
quantification}

{\label{112264}}

In general, we felt that more details about experimental and analytical
protocols were needed for the reader. For example, some of the analysis
could be affected by photobleaching, such as the translocation speed in
shorter cells.

\par\null

\subsubsection*{Regarding simulations}

{\label{728580}}

We had some difficulty interpreting the simulation methods; we would
like to have more information on the simulation algorithm and initial
conditions in addition to the model, ideally with code made available.
We assumed the simulations were similar to Chaudhuri 2012 PRL, with
crowding molecules and confinement volume increased at some defined time
steps. It was also not clear how the cell walls are moved upon
stretching. Is it relative to the chromosome position or to the cell
center, or to some other reference?

\par\null

We wondered whether chromosome positioning at the \selectlanguage{ngerman}½ or ¼ and ¾ positions
is an inevitable consequence of (1) how crowding molecules were added
and (2) a near impossibility of crowding molecules moving from one pole
to the other (Simulation averages in Fig 3D and 6B, and the snapshot in
S3A, show zero crowding density within the DNA). Regarding (1) the Widom
insertion parameters seem likely to yield equal rates of insertion on
either side of the chromosome; because of (2) the system then naturally
evolves to a~centered chromosome position. In the presence of two
chromosomes insertion between the chromosomes is twice as likely,
yielding an inter chromosome excluded volume twice a large as the polar
volumes. Chromosome positioning then seems a consequence of model design
choices. It would be interesting to discuss those in their physiological
context: can the chromosome be considered an impassable plug for crowder
molecules? Are such molecules expected to be equally expressed on either
side of the chromosome? And could this hypothetical crowder
compartmentalization by the chromosome have other physiological
consequences?~

\subsection*{Minor concerns}

{\label{165475}}

\begin{itemize}
\tightlist
\item
  Figure 1: 4585 for 12 minutes intervals, this makes 212 cells. Maybe
  this should be clearly stated.
\item
  Figure 1: Journal club attendees asked for a graph of the different
  cell length distribution, since it seems that cells longer than 17 um
  are becoming rare.
\item
  Figure 2: Why are there two ter sites at some time points (69', 75',
  81', 96')?
\item
  Figure S3: An overlay image showing cell contours determined from
  phase contrast or membrane dye would help to visualize the poles.
  Maybe 3D-SIM would help to clearly see the helix?
\item
  Journal club members would have appreciated more details about the
  roles of hns, slmA, and fis; e.g. how slmA-FtsZ interaction and fis
  transcription regulation could impact the chromosome extent.
\end{itemize}

\subsection*{Technical notes}

{\label{885310}}

\begin{itemize}
\tightlist
\item
  Page 7, line 31, typo ``local DNA''
\item
  Figure S1: Legends for C and D are inverted
\end{itemize}

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