I have had 4 mains sequences with overlapping and I have published 182 papers.  UMR5558

Here are only the milestones steps.

Immunochemistry of Staphylococcus aureus

• The isolation and characterization of various protein (Flandrois, Fleurette, & Modjadedy, 1975; Grov, Flandrois, Fleurette, & Oeding, 1978) or polysaccharides (Ndulue & Flandrois, 1983) was the following of my PhD Thesis. I have also described the affinity of the cells to human proteins (Carret et al., 1985).

• A side effect of this research has been a world-wide used affinity reagent (Carret, Flandrois, Bismuth, & Saulnier, 1982) (“StaphySlide”) that remains, in a revised version, the basis of most of the immediate identification reagents for Staphylococcus aureus (photography above: StaphySlide, the red-cells covered with fibrinogen and S.aureus adhering).

Modelling of bacteria growth

Applications to antibiotics sensitivity and food safety

• Modelling of bacteria growth was made possible by the early development of informatics. My team was involved in the mathematical approach and optimal production of biological datas. we have demonstrate the change of growth model occuring when bacteria are exposed to the drugs and described the mathematical law linking growth rate and other parameters and antibiotics concentration. This was done both for sub-inhibitory concentrations (Comby, Flandrois, Carret, & Pichat, 1988) and lethal concentrations (Guérillot, Carret, & Flandrois, 1993). A major paper describe the interpretation of the antibiotic effect in term of maintenance energy for the cell (Lobry, Carret, & Flandrois, 1992).

• The applications were not possible in real life due to the need of a dedicated high throughput performance photometer. We described also how photometry combined with mathematical modelling is able to study the swelling of the micro-organisms during the lag phase. The possibility to use our algorithms is now studied by research teams using the new “digital microbiology” concept.

• Aside this extensive model approach, I have developed the firrst “expert systems” to analyse and automatically correct the result of antibiotics susceptibility testing (Comby, Flandrois, & Pave, 1988). These “partially intelligent” programs are now included in each antibiotic susceptibility systems and derived from this original work.

• I oriented in parallel the team on the basic physiology of bacteria and we described then the biological-mathematical laws linking growth rate and latency to pH and temperature (Rosso, Lobry, Bajard, & Flandrois, 1995). More, we have discovered a fundamental law in the bacteria linking the optimum, minimum and maximum temperature of growth (Rosso, Lobry, & Flandrois, 1993). A lot of work was also done to model interactions between bacteria (especially those found in food, pathogens vs non pathogens) (Cornu, Kalmokoff, & Flandrois, 2002).

• There results and more works (Bréand, Flandrois, Rosso, Tomassone, & Fardel, 1997) were applied to the prediction of growth of bacteria in food in cooperation with Danone. The prediction of growth of pathogens in food is good at months level (up to 3 months). This “predictive microbiology” is now widely used in agro-food industry.

• Predictive microbiology is a part of the risk-analysis process in food, environment... (figure : simulation of the growth of Listeria monocytogenes in food with variable temperatures)

New methods for bacteria detection/enumeration

• This topic has been important all over my work, partly due to my position as Head of a diagnostic laboratory.

• I have been involved in patents concerning biomolecular detection of pathogens, new detection methods in food microbiology and use of digital microbiology in bacteria enumeration.

• This applied scientific research is my main preoccupation today:

• What is important for me is that the two project have similar probability issues : the binomial law is to take into account and statistical signification of a given level of detection (especially 0) has to be accurately computed to compare the results. Earlier studies of my team on blood culture results were dealing with the same problem (Lamy 2002, Leyssene, 2012).

Bioinformatics applied to bacteria identification

This is the beginning of the on-going work

• The main result was the “BIBi” project (Devulder, Perriere, Baty, & Flandrois, 2003, Flandrois, Gouy and Perrière 2014) . I demonstrate that Bacteria Identification based on Bioinformatics (BIBi) was possible and easy to use in routine (S Mignard & Flandrois, 2006) if a convenient database was built. This program is available on the web and I recently release the mark 5 version using new algorithms to build the database and extract the pertinent information. Annually 50000 identi cations are done by the system and it is cited in 92 papers.

• As the Mycobacterium genus was the model genus that I use to develop BIBi (Devulder, Pérouse de Montclos, & Flandrois, 2005), I improve the phylogeny and taxinomic analysis of this genus by combining bioinformatics methods (Mignard & Flandrois, 2008, Guérin et al. 2014, Pin 2014). .

Bibliography for the above-cited works


  • Baty, F., Ritz, C., Charles, S., Brutsche, M., Flandrois, J.- P., and Delignette-Muller, M.-L. (2015). A toolbox for nonlinear regression in R : The package nlstools. Journal of Statistical Software, 66(5) :1 21.
  • Bechy-Loizeau, A.-L., Flandrois, J.-P., and Abai- bou, H. (2015). Assessment of polycarbonate filter in a molecular analytical system for the microbiological quality monitoring of recycled waters onboard ISS. Life Sciences in Space Research, 6 :29 35.
  • Bréand, S., Flandrois, J. P., Rosso, L., Tomassone, R., & Fardel, G. (1997). A model describing the relationship between lag time and mild temperature increase duration. Int J Food Microbiol, 38(2-3), 157–167.
  • Carret, G., Emonard, H., Fardel, G., Druguet, M., Herbage, D., & Flandrois, J. P. (1985). Gelatin and collagen binding to Staphylococcus aureus strains. Ann Inst Pasteur Microbiol, 136A(2), 241–245 (Corresponding to the figure) above.
  • Carret, G., Flandrois, J. P., Bismuth, R., & Saulnier, M. (1982). Relative value of staphylocoagulase and fibrinogen affinity for the identification of Staphylococcus aureus. J Appl Bacteriol, 53(3), 351–354.
  • Comby, S., Flandrois, J. P., Carret, G., & Pichat, C. (1988). Mathematical modelling of bacterial growth at subinhibitory levels of aminoglycosides. Ann Inst Pasteur Microbiol, 139(5), 613–629.
  • Comby, S., Flandrois, J. P., & Pave, A. (1988). [An expert system as an aid to the validation of results of the antibiogram. Feasibility study based on the example of Staphylococcus aureus]. Pathol Biol, 36(5), 381–385.
  • Cornu, M., Kalmokoff, M., & Flandrois, J.-P. (2002). Modelling the competitive growth of Listeria monocytogenes and Listeria innocua in enrichment broths. Int J Food Microbiol, 73(2-3), 261–274.
  • Devulder, G., Perriere, G., Baty, F., & Flandrois, J. P. (2003). BIBI, a Bioinformatics Bacterial Identification Tool. Journal of Clinical Microbiology, 41(4), 1785–1787. doi:10.1128/JCM.41.4.1785-1787.2003
  • Devulder, G., Pérouse de Montclos, M., & Flandrois, J. P. (2005). A multigene approach to phylogenetic analysis using the genus Mycobacterium as a model. International journal of systematic and evolutionary microbiology, 55(Pt 1), 293–302. doi:10.1099/ijs.0.63222-0
  • Flandrois, J. P., Fleurette, J., & Modjadedy, A. (1975). Comparative study on two methods for serotyping of Staphylococcus aureus: the Pillet method and the Oeding method. II.-Possible identity between Pillet’s antigen 9 and Oeding's antigen h1. Ann Microbiol (Paris), 126(3), 333–342.
  • Flandrois, J.-P., Lina, G., and Dumitrescu, O. (2014). Mubii-tb-db : a database of mutations associated with antibiotic resistance in mycobacterium tuberculosis. BMC bioinformatics, 15(1) :107.
  • Flandrois, J.-P., Perrière, G., and Gouy, M. (2015). lebibiqbpp : a set of databases and a webtool for automatic phylogenetic analysis of prokaryotic sequences. BMC Bioinformatics, 16(1) :1 12.
  • Guérin-Faublée, V., Flandrois, J.-P., Pichat, C., Boschiroli, M. L., and Lamy, B. (2013). Mycobacterium bourgelatii sp. nov., a rapidly growing, non-chromogenic species isolated from the lymph nodes of cattle. International journal of systematic and evolutionary microbiology, 63(12) :4669 4674.
  • Grov, A., Flandrois, J. P., Fleurette, J., & Oeding, P. (1978). Immunochemical studies on the specific agglutinogens of Staphylococcus aureus. I. Isolation and characterization of antigen h1. Acta pathologica et microbiologica Scandinavica Section B, Microbiology, 86B(3), 143–147.
  • Guérillot, F., Carret, G., & Flandrois, J. P. (1993). A statistical evaluation of the bactericidal effects of ceftibuten in combination with aminoglycosides and ciprofloxacin. J Antimicrob Chemother, 32(5), 685–694.
  • Junillon, T., Morand, L., and Flandrois, J.-P. (2014a). Enhanced tetrazolium violet reduction of salmonella spp. by magnesium ad- dition to the culture media. Food microbiology, 42 :132 135.
  • Junillon, T., Mosticone, D., Mallen, B., Baril, F., Morand, L., Michel, D., and Flandrois, J.-P. (2014b). Optimization of the reactional medium and a food impact study for a colorimetric in situ sal- monella spp. detection method. International journal of food microbiology, 181 :48 52.
  • Junillon, T. and Flandrois, J.-P. (2014c). Di- minution of 2, 3, 5-triphenyltetrazolium chloride toxicity on listeria monocy- togenes growth by iron source addition to the culture medium. Food micro- biology, 38 :1 5.
  • Pin, D., Guérin-Faublée, V., Garreau, V., Breysse, F., Dumi- trescu, O., Flandrois, J.-P., and Lina, G. (2014). Mycobacterium species related to m. leprae and m. lepromatosis from cows with bovine nodular the- litis. Emerging Infectious Diseases, 20(12) :2111 2114.
  • Lamy, B, Roy P, Carret G, Flandrois JP, Delignette-Muller ML. What is the relevance of obtaining multiple blood samples for culture? A comprehensive model to optimize the strategy for diagnosing bacteremia. Clin Infect Dis. 2002 Oct 1;35(7):842-50. Epub 2002 Sep 10.
  • Leyssene D, Gardes S, Vilquin P, Flandrois JP, Carret G, Lamy B. Species-driven interpretation guidelines in case of a single-sampling strategy for blood culture. Eur J Clin Microbiol Infect Dis. 2011 Dec;30(12):1537-41. doi: 10.1007/s10096-011-1257-3. Epub 2011 Apr 18
  • Lobry, J. R., Carret, G., & Flandrois, J. P. (1992). Maintenance requirements of Escherichia coli ATCC 25922 in the presence of sub-inhibitory concentrations of various antibiotics. J Antimicrob Chemother, 29(2), 121–127.
  • Mignard, S, & Flandrois, J. P. (2006). 16S rRNA sequencing in routine bacterial identification: a 30-month experiment. J Microbiol Methods, 67(3), 574–581. doi:10.1016/j.mimet.2006.05.009
  • Mignard, Sophie, & Flandrois, J.-P. (2008). A seven-gene, multilocus, genus-wide approach to the phylogeny of mycobacteria using supertrees. Int J Syst Evol Microbiol, 58(Pt 6), 1432–1441. doi:10.1099/ijs.0.65658-0
  • Ndulue, A. N., & Flandrois, J. P. (1983). Immunochemical studies of Staphylococcus aureus Oeding-Haukenes antigen a5: a phosphorus-containing polysaccharide. J Gen Microbiol, 129(12), 3603–3610.
  • Rosso, L., Lobry, J., Bajard, S., & Flandrois, J. (1995). Convenient Model To Describe the Combined Effects of Temperature and pH on Microbial Growth. Appl Environ Microbiol, 61(2), 610–616.
  • Rosso, L., Lobry, J. R., & Flandrois, J. P. (1993). An unexpected correlation between cardinal temperatures of microbial growth highlighted by a new model. J Theor Biol, 162(4), 447–463. doi:10.1006/jtbi.1993.1099
  • Bréand S., Fardel G., Flandrois, J. P., Rosso, L., & Tomassone, R. (1999). A model describing the relationship between regrowth lag time and mild temperature increase for Listeria monocytogenes. Int J Food Microbiol, 46(3), 251–261.