Single-cell analysis of the glucose/lactose diauxic shift in E. coli

This is a companion website describing the data analysis underlying the article Subpopulations of sensorless bacteria drive fitness in fluctuating environments.

This project consists for a large part of single-cell experiments done using microfluidics:

• Lags estimation
• Controls
• Induction and memory of the native lac operon
• Perturbations of the repressed lac operon expression
• lac induction at lower lactose concentrations
• Simulation of population lags from distribution of single-cell lags

In addition, we used an array of other techniques and analysis:

• Fluorescence lifetime experiments
• Population lags in diauxie experiments
• Identification of SMT candidates in MS data

Available material includes:

• raw image datasets, as well as images processed for analysis (https://doi.org/10.17867/10000149),
• data tables obtained from image analysis (https://doi.org/10.5281/zenodo.3894719),
• analysis source code and additional data (https://github.com/julou/MoM_lacInduction).

Mother Machine experiments

In typical experiments, E. coli is grown in a Dual-Input Mother Machine where glucose and lactose alternate every 4 hours:

Dataset description

mygl <- myframes %>% ungroup() %>% 
  filter(!discard_top, !discard_start) %>% 
  mutate(label=rename_conds(condition)) %>% 
  # start from the total number of observations
  group_by(condition, label, date, pos, gl) %>%
  summarise(n_obs=n()) %>%
  # add the number of dividing cells
  left_join(myframes %>%
              ungroup() %>% 
              filter(!discard_top, end_type=='div') %>% 
              group_by(date, pos, gl, id) %>% 
              filter(!any(discard_start)) %>% 
              slice(1) %>% 
              group_by(date, pos, gl) %>% 
              summarise(n_div_cells=n()) ) %>%
  # add the number of frames
  left_join(myframes %>%
              group_by(date, pos, gl) %>% 
              summarise(nframes=max(frame)) )

(mytables[['expts_list']] <- mygl %>% ungroup() %>% 
   # mutate(condition=factor(condition, levels=unique(condition_acq_times$condition)) ) %>% 
   group_by(condition, label, date) %>%
   summarise(n_lanes=length(unique(interaction(date, pos, gl))),
             # n_div_cells=sum(is.na(n_div_cells)),
             n_div_cells=sum(n_div_cells),
             n_obs=sum(n_obs) ) %>% 
   left_join(
     mycells_switching %>% 
       ungroup %>% 
       filter(! date %in% discarded_dates) %>% 
       group_by(condition, date) %>%
       summarise(
         n_switch=n(),
         n_lags=sum(!is.na(lag_200)),
         n_discard=sum(logl_time_slope_before <= min_growth_rate, na.rm=TRUE) ) %>% 
       mutate(n_discard=ifelse(condition=='switch_gly_lac', NA, n_discard) )
   )
) %>% 
  filter(! date %in% discarded_dates) %>% 
  knitr::kable() %>% 
  kableExtra::kable_styling() %>% 
  identity()

condition	label	date	n_lanes	n_div_cells	n_obs	n_switch	n_lags	n_discard
glucose	glucose	20150616	31	2021	92270	NA	NA	NA
glucose	glucose	20150617	30	1920	91276	NA	NA	NA
lactose	lactose	20150624	30	1649	86776	NA	NA	NA
lactose	lactose	20150630	30	1671	85949	NA	NA	NA
mg1655	mg1655	20150812	6	364	17283	NA	NA	NA
switch_04h	memory 4h	20150703	28	1431	76295	462	445	3
switch_04h	memory 4h	20150708	30	1600	88410	536	511	6
switch_06h	memory 6h	20151204	30	1848	107195	548	524	10
switch_08h	memory 8h	20180206	31	NA	66894	332	312	1
switch_12h	memory 12h	20180207	30	1517	84568	353	340	3
switch_12h	memory 12h	20180216	30	1633	82626	344	329	4
switch_16h	memory 16h	20160912	39	2437	134488	444	419	8
switch_20h	memory 20h	20161014	34	2224	133238	382	355	10
switch_24h	memory 24h	20161007	31	2343	135928	350	334	6
switch_glcLac_lac	glcLac lac	20171114	31	842	47798	180	171	0
switch_glcLac_lac	glcLac lac	20180108	31	804	50630	174	170	4
switch_gly_lac	glyc > lac	20170919	26	139	28832	137	123	NA
switch_gly_lac	glyc > lac	20170920	29	NA	32475	142	132	NA
switch_lac001_10h	lac001 10h	20190614	24	580	27973	115	105	1
switch_lac001_6h	lac001 6h	20190605	38	528	25028	193	178	1
switch_lacIoe	lacIoe	20180116	31	796	55447	177	161	0
switch_lacIoe	lacIoe	20180214	31	761	46967	157	142	1
switch_lacIoe_preIPTG10uM	lacIoe preIPTG10uM	20180604	33	410	28272	174	160	1
switch_lacIoe_withIPTG10uM	lacIoe withIPTG10uM	20180119	30	572	37135	162	158	0
switch_lacIPTG5uM	lacIPTG5uM	20180316	32	572	35363	182	172	0
switch_lactose_priming	lactose priming	20161212	39	269	28142	230	214	3
switch_late	late	20180516	30	2370	104792	166	155	0
switch_preIPTG5uM	preIPTG5uM	20180514	31	385	28585	178	167	0
switch_preIPTG5uM	preIPTG5uM	20180531	29	410	26780	170	161	0
switch_ramp40min	ramp40min	20171121	30	371	29252	164	154	1
switch_ramp40min	ramp40min	20180319	32	496	33684	195	185	1
switch_withIPTG1uM	withIPTG1uM	20161130	41	442	36900	225	212	0
switch_withIPTG5uM	withIPTG5uM	20161207	32	438	28738	178	175	2
switch_withIPTG5uM	withIPTG5uM	20180122	30	431	27985	173	168	0

Colophon

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