Strain and plasmid
The strain used in this study was Escherichia coli W3110 recA
−. In such a strain, the recA gene was interrupted by the cat (chloramphenicol acetyl-transferase) gene in our laboratory according to the methodology described by Datsenko and Wanner [12]. The chloramphenicol resistance cassette was amplified from the pKD3 plasmid using the forward primer, ATGCGACCCTTGTGTATCAAACAAGACGATTAAAAATCTTCGTTAGTTTCGTGTAGGCTGGAGCTGCTTC, and the reverse primer, CAGAACATATTGACTATCCGGTATTACCCGGCATGACAGGAGTAAAAATGATGGGAATTAGCCATGGTCC. The underlined and non-underlined regions are the homologous sequences to the pKD3 plasmid and recA gene, respectively. The interruption of the recA gene was confirmed by polymerase chain reaction PCR. E. coli W3110 recA
− was probed to double the SCF compared with wild-type E. coli W3110 (data not shown). The plasmid pVAX1 (Thermo Fisher Scientific, Waltham, MA, USA) was used as a pDNA vaccine-model in our study due to its widespread use in DNA vaccine development. It is a 3-kb high-copy number vector that confers kanamycin resistance for the selection in E. coli.
Growth conditions
The medium composition (in g/L) was as follows: glucose, 10; K2HPO4, 17; KH2PO4, 5.3; (NH4)2SO4, 2.5; NH4Cl, 1.0; Citrate-Na3·2H2O, 2; MgSO4·7H2O, 1.0; Thiamine-HCl, 0.01; and trace element solution, 2 mL/L; and 50 μg/mL kanamycin sulfate. The trace element solution composition (in g/L) was ZnCl2, 10.5; EDTA, 5.5; CoSO4·7H2O, 1.5; MnSO4·H2O, 6.4; CuSO4·5H2O, 1.1; H3BO3, 1.5; Na2MoO4·2H2O, 1; FeCl3·6H2O, 51.4; and Cit-H·H2O, 39.9. The cultures were carried out in 500 mL of medium in a 1-L Biostat A Plus stirred-tank bioreactor (Sartorius BBI, Melsungen, Germany) at 37 °C. The pH was set at 7.2 and was controlled by the addition of 15% NH4OH. DOT was measured using a polarographic sensor (Hamilton, Reno, NV). The sensor was calibrated by flowing pure N2 (for 0% air sat.) or air (for 100% air sat.) at 1 vvm. The DOT sensor was cleaned and filled with fresh electrolyte (Oxylyte, Hamilton, Reno, NV) previous to each culture. DOT was controlled at 3 or 30% air sat. by a PI controller in the agitation cascade mode (t
i
= 50 s; x
p
= 140%; t
D
= 0 s; dead band = 0.1%) using MFCS/DA software (Sartorius BBI, Melsungen, Germany). For oscillated DOT cultures, the stirrer speed was shifted from 100 to 1200 rpm every 10 min. Air was supplied at 1 vvm for aerobic and oscillated cultures and at 0.25 vvm for microaerobic cultures. Off-gas composition was monitored on-line through a BlueInOne Ferm (BlueSens, Herten, Germany) gas analyzer. Three independent cultures under each condition were performed.
Off-line analyses
The biomass concentration was determined as the dry cell weight. Extracellular metabolites were quantified from filtered (0.2 μm cellulose acetate membranes) supernatants. Glucose and ethanol were quantified in a YSI 2700 biochemistry analyzer (YSI Inc., OH, USA). Organic acids were analyzed by HPLC using a Bio-Rad Aminex HPX-87H column (Bio-Rad Laboratories Inc., CA, USA) at 50 °C and 0.4 mL/min of 5 mM H2SO4, and a UV detector set at 210 nm.
OTR, CTR and RQ calculations
From the off-gas composition data, OTR and CTR were calculated as follows:
$$ OTR=\frac{P_i}{R{ T}_i}\frac{F_i}{V_L}\left({y}_{O_2, i}-{R}_I{y}_{O_2, o}\right) $$
(1)
$$ C T R=\frac{P_i}{R{ T}_i}\frac{F_i}{V_L}\left({R}_I{y}_{C{ O}_2, o}-{y}_{C{ O}_2, i}\right) $$
(2)
$$ {R}_I=\frac{1 - {y}_{O_2, i}-{y}_{CO_2, i} - {y}_{H_2 O, i}}{1-{y}_{O_2, o} - {y}_{CO_2, o}-{y}_{H_2 O, o}} $$
(3)
where:
-
OTR, oxygen transfer rate (mmol/L/h);
-
CER, carbon dioxide volumetric production rate (mmol/L/h);
-
p, absolute pressure of the gaseous stream, in bar;
-
F, volumetric flow rate of the gaseous stream (L/h);
-
R, ideal gas constant (0.0821 bar L K−1 mol−1);
-
V
L
, liquid volume (L);
-
T, temperature of the gaseous stream (K);
-
\( {y}_{O_2} \), oxygen molar fraction in the gaseous stream;
-
\( {y}_{CO_2} \), carbon dioxide molar fraction in the gaseous stream;
-
\( {y}_{H_2 O} \), water molar fraction in the gaseous stream;
-
R
I
, inert ratio;
-
i and o subscripts denote at inlet and outlet, respectively.
The specific rates q
O2
and q
CO2
were determined by plotting OTR and CER, respectively, against the biomass concentration (X), and obtaining the slope from the line of best fit by the least squares method. Only data from the period where DOT was constant was used.
For the oscillated cultures, where such conditions were not met, the global specific uptake rates were calculated as follows:
$$ {q}_{O_2}=\frac{\int OTR\ (t) dt}{X} $$
(4)
$$ {q}_{O_2}=\frac{\int CTR(t) dt}{X} $$
(5)
For all cases, RQ was calculated as the ratio,
$$ R Q=\frac{\int CTR(t) dt}{\int OTR(t) dt} $$
(6)
Numerical integrations were computed by SigmaPlot 12.5 Area Below Curves Macro.
Metabolic fluxes estimation
Flux balance analysis (FBA)
The flux distribution in the metabolic network was calculated based on a linear programming algorithm, using the specific uptake rates and specific production rates as inputs for the calculations (Flux Balance Analysis) [13]. The network studied here comprised 103 reactions and 76 metabolites (intracellular and extracellular) covering glycolysis, pentose phosphate, tricarboxylic acid (TCA) cycle, and mixed-acid fermentation pathways. It included reactions for transport and exchange, plus biomass and plasmid synthesis objective functions. The extracellular exchange of pyruvate and malate were considered to be inactive. Simulations were run using MatLab. Fluxes were constrained according to the reversibility of the reactions. The reaction rate of formate hydrogen-lyase (FHL) was constrained to 0 in all simulations. Formate decomposition into CO2 and H2 seems not to be a plausible reaction because the mineral media was devoid of selenium and nickel, which are required for the catalytic activity of FHL [14].
Sensitivity analysis
Sensitivity analysis was performed to evaluate the biomass function response to changes in the two measured input fluxes (\( {q}_{O_2} \)and q
s
). Simulations to maximize the biomass by changing \( {q}_{O_2} \) and q
S
fluxes were run. The results are provided as Additional files.
Time-point flux balance analysis
To analyze the metabolic effect of the non-steady state condition of the oscillated cultures, flux balance analysis was carried out for biomass maximization at every time-point of the culture. The O2 and CO2 fractions in the exhaust gas were used as data inputs. O2 and CO2 fluxes were calculated by dividing CTR and OTR by the biomass concentration. The latter was obtained from a second-order polynomial fit to the experimental biomass cell dry weight concentration and time data. Spreadsheets detailing the calculations, constraints and results, as well as the Matlab code, are provided as Additional files.
pDNA analysis
pDNA was isolated and purified from 5.8 mg of wet biomass using the QIAprep Spin Miniprep Kit (Qiagen, Hilden, Germany), and recovered in 70 μL of EB buffer at 70 °C. Such procedure enabled to maximize the amount of pDNA extracted from cells (data not shown), whereas SCF is not expected to be influenced, as indicated by the manufacturer. The extracted pDNA was quantified in a Nanodrop 2000 system. The SCF was determined from the image analysis of 0.8% agarose gels pre-stained with SYBR green safe (Invitrogen, Carlsbad, CA, USA). Additionally, pDNA samples were analyzed by chip-electrophoresis in a Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA, USA) using the Agilent DNA 7500 kit. Prior to the run, the samples were concentrated by lyophilization (500–900 ng/μL) to obtain fluorescence signals within the reading capabilities of the equipment. pDNA samples from the master cell bank and the different production conditions were sequenced. pDNA sequencing and assembly were performed using the Genome Analyzer II (Illumina, CA, USA) and Velvet 1.2.0 program, respectively. The resulting assembled sequences were aligned with the reported reference sequence of the pVAX1 plasmid (Thermo Fisher Scientific, Waltham, MA, USA) using the BLASTN 2.6.1+ suite [15] (NCBI, USA). Additionally, sequences were also aligned by ClustalW and LALING [16] to compare and corroborate the results obtained from the different algorithms. pDNA sequencing and assembly were performed at the Unidad de Secuenciación Masiva of the Universidad Nacional Autónoma de México and the Laboratorio de Servicios Genómicos of the Laboratorio Nacional de Genómica para la Biodiversidad, México.