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Surface conditioning with Escherichia coli cell wall components can reduce biofilm formation by decreasing initial adhesion

  • Received: 14 April 2017 Accepted: 11 July 2017 Published: 18 July 2017
  • Bacterial adhesion and biofilm formation on food processing surfaces pose major risks to human health. Non-efficient cleaning of equipment surfaces and piping can act as a conditioning layer that affects the development of a new biofilm post-disinfection. We have previously shown that surface conditioning with cell extracts could reduce biofilm formation. In the present work, we hypothesized that E. coli cell wall components could be implicated in this phenomena and therefore mannose, myristic acid and palmitic acid were tested as conditioning agents. To evaluate the effect of surface conditioning and flow topology on biofilm formation, assays were performed in agitated 96-well microtiter plates and in a parallel plate flow chamber (PPFC), both operated at the same average wall shear stress (0.07 Pa) as determined by computational fluid dynamics (CFD). It was observed that when the 96-well microtiter plate and the PPFC were used to form biofilms at the same shear stress, similar results were obtained. This shows that the referred hydrodynamic feature may be a good scale-up parameter from high-throughput platforms to larger scale flow cell systems as the PPFC used in this study. Mannose did not have any effect on E. coli biofilm formation, but myristic and palmitic acid inhibited biofilm development by decreasing cell adhesion (in about 50%). These results support the idea that in food processing equipment where biofilm formation is not critical below a certain threshold, bacterial lysis and adsorption of cell components to the surface may reduce biofilm buildup and extend the operational time.

    Citation: Luciana C. Gomes, Joana M. R. Moreira, José D. P. Araújo, Filipe J. Mergulhão. Surface conditioning with Escherichia coli cell wall components can reduce biofilm formation by decreasing initial adhesion[J]. AIMS Microbiology, 2017, 3(3): 613-628. doi: 10.3934/microbiol.2017.3.613

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  • Bacterial adhesion and biofilm formation on food processing surfaces pose major risks to human health. Non-efficient cleaning of equipment surfaces and piping can act as a conditioning layer that affects the development of a new biofilm post-disinfection. We have previously shown that surface conditioning with cell extracts could reduce biofilm formation. In the present work, we hypothesized that E. coli cell wall components could be implicated in this phenomena and therefore mannose, myristic acid and palmitic acid were tested as conditioning agents. To evaluate the effect of surface conditioning and flow topology on biofilm formation, assays were performed in agitated 96-well microtiter plates and in a parallel plate flow chamber (PPFC), both operated at the same average wall shear stress (0.07 Pa) as determined by computational fluid dynamics (CFD). It was observed that when the 96-well microtiter plate and the PPFC were used to form biofilms at the same shear stress, similar results were obtained. This shows that the referred hydrodynamic feature may be a good scale-up parameter from high-throughput platforms to larger scale flow cell systems as the PPFC used in this study. Mannose did not have any effect on E. coli biofilm formation, but myristic and palmitic acid inhibited biofilm development by decreasing cell adhesion (in about 50%). These results support the idea that in food processing equipment where biofilm formation is not critical below a certain threshold, bacterial lysis and adsorption of cell components to the surface may reduce biofilm buildup and extend the operational time.


    1. Introduction and the main result

    Nowadays, mathematics is useful in many things, for example, physics, chemistry, biology, computer, medical, architecture, and so on (see e.g., [3, 7, 14]). Here we focus on biology. One of the important models in biology is the logistic equation ut=u(1-u). Some of biological models have the logistic term, e.g., the Fisher-KPP equation

    ut=Δu+u(1u).

    On the other hand, many mathematicians study a chemotaxis system lately, which describes a part of the life cycle of cellular slime molds with chemotaxis. After the pioneering work of Keller-Segel [8], a number of variations of the chemotaxis system are proposed and investigated (see e.g., [2, 4, 5]). Also, multi-species chemotaxis systems have been studied by e.g., [6, 15]. In this paper we focus on a twospecies chemotaxis system with logistic term which describes a situation in which multi populations react on a single chemoattractant.

    We consider the two-species chemotaxis system

    {ut=Δu(uχ1(w)w)+μ1u(1u),xΩ,t>0,vt=Δv(vχ2(w)w)+μ2v(1v),xΩ,t>0,wt=dΔw+h(u,v,w),xΩ,t>0,un=vn=wn=0,xΩ,t>0,u(x,0)=u0(x),v(x,0)=v0(x),w(x,0)=w0(x),xΩ, (1.1)

    where Ω is a bounded domain in RN (NN) with smooth boundary Ω and n denotes the unit outer normal vector of Ω. The initial data u0, v0 and w0 are assumed to be nonnegative functions. The unknown functions u(x, t) and v(x, t) represent the population densities of two species and w(x, t) shows the concentration of the substance at place x and time t.

    In mathematical view, global existence and behavior of solutions are fundamental theme. Recently, Negreanu-Tello [12, 13] built a technical way to prove global existence and asymptotic behavior of solutions to (1.1). In [13] they dealt with (1.1) when d=0, µi > 0 under the condition

    ˉww0;h(ˉu,ˉv,ˉw)0,

    where ˉu, ˉv satisfy some representations determined by ˉw. In [12] they studied (1.1) when 0 < d < 1, µi=0 under similar conditions as in [13] and

    χi+11dχ2i0(i=1,2). (1.2)

    They supposed in [12, 13] that the functions h, χi for i=1, 2 generalize of the prototypical case χi(w)=Ki(1+w)σi (Ki>0,σi1), h(u,v,w)=u+vw. These days, the restriction of 0≤d < 1 for global existence is completely removed and asymptotic stability of solutions to (1.1) is established for the first time under a smallness condition for the function χi generalizing of χi(w)=Ki(1+w)σi (Ki>0,σi>1) ([11]).

    The purpose of this paper is to improve a way in [11] for obtaining asymptotic stability of solutions to (1.1) under a more general and sharp smallness condition for the sensitivity function χi(w). We shall suppose throughout this paper that h, χi (i=1, 2) satisfy the following conditions:

    χiC1+ω([0,))L1(0,)(0<ω<1),χi>0(i=1,2), (1.3)
    hC1([0,)×[0,)×[0,)),h(0,0,0)0, (1.4)
    γ>0; hu(u,v,w)0,hv(u,v,w)0,hw(u,v,w)γ, (1.5)
    δ>0,M>0;|h(u,v,w)+δw|M(u+v+1), (1.6)
    ki>0;χi(w)h(0,0,w)ki(i=1,2). (1.7)

    We also assume that

    p>N; 2dχi(w)+((d1)p+(d1)2p2+4dp)[χi(w)]20(i=1,2). (1.8)

    The above conditions cover the prototypical example χi(w)=Ki(1+w)σi (Ki>0, σi>1), h(u,v,w)=u+vw. We assume that the initial data u0, v0, w0 satisfy

    0u0C(ˉΩ){0}, 0v0C(ˉΩ){0}, 0w0W1,q(Ω)(q>N). (1.9)

    The following result which is concerned with global existence and boundedness in (1.1) was established in [11].

    Theorem 1.1 ([11, Theorem 1.1]). Let d≥0, µi > 0 (i=1, 2). Assume that h, χi satisfy (1.3)-(1.8). Then for any u0, v0, w0 satisfying (1.9) for some q > N, there exists an exactly one pair (u, v, w) of nonnegative functions

    u,v,wC(ˉΩ×[0,))C2,1(ˉΩ×(0,))when d>0,u,v,wC([0,);W1,q(Ω))C1((0,);W1,q(Ω))when d=0,

    which satisfy (1.1). Moreover, the solution (u; v; w) is uniformly bounded, i.e., there exists a constant C1 > 0 such that

    u(t)L(Ω)+v(t)L(Ω)+w(t)L(Ω)C1forall t0.

    Since Theorem 1.1 guarantees that u, v and w exist globally and are bounded and nonnegative, it is possible to define nonnegative numbers α, β by

    α:=max(u,v,w)Ihu(u,v,w),β:=max(u,v,w)Ihv(u,v,w), (1.10)

    where I=(0, C1)3 and C1 is defined in Theorem 1.1.

    Now the main result reads as follows. The main theorem is concerned with asymptotic stability in (1.1).

    Theorem 1.2. Let d > 0, µi > 0 (i=1, 2). Under the conditions (1.3)-(1.9) and

    α>0,β>0,χ1(0)2<16μ1dγα2+β2+2αβ,χ2(0)2<16μ2dγα2+β2+2αβ, (1.11)

    the unique global solution (u, v, w) of (1.1) satisfies that there exist C > 0 and λ>0 such that

    u(t)1L(Ω)+v(t)1L(Ω)+w(t)˜wL(Ω)Ceλt(t>0),

    where ˜w0 such that h(1, 1, ˜w)=0.

    Remark 1.1. This result improves the previous result [11, Theorem 1.2]. Indeed, the condition (1.11) is sharper than“χi(0) are suitably small”assumed in [11]. Moreover, this result attains to show the convergence rate which cannot be given in [11].

    Remark 1.2. From (1.4)-(1.6) there exists ˜w0 such that h(1,1,˜w)=0. Indeed, if we choose ˉw3M/δ, then (1.6) yields that h(1,1,ˉw)3Mδˉw0. On the other hand, (1.4) and (1.5) imply that h(1, 1, 0)≥h(0, 0, 0)≥0. Hence, by the intermediate value theorem there exists ˜w0 such that h(1, 1, ˜w)=0.

    The strategy for the proof of Theorem 1.2 is to modify an argument in [10]. The key for this strategy is to construct the following energy estimate which was not given in [11]:

    ddtE(t)ε(Ω(u1)2+Ω(v1)2+Ω(w˜w)2)

    with some function E(t)≥0 and some ε>0. This strategy enables us to improve the conditions assumed in [11].


    2. Proof of the main result

    In this section we will establish asymptotic stability of solutions to (1.1). For the proof of Theorem 1.2, we shall prepare some elementary results.

    Lemma 2.1 ([1, Lemma 3.1]). Suppose that f : (1, ∞)→R is a uniformly continuous nonnegative function satisfying 1f(t)dt<. Then f(t)0 as t.

    Lemma 2.2. Let a1,a2,a3,a4,a5R. Suppose that

    a1>0,a3>0,a5a224a1a244a3>0. (2.1)

    Then

    a1x2+a2xz+a3y2+a4yz+a5z20 (2.2)

    holds for all x,y,zR.

    Proof. From straightforward calculations we obtain

    a1x2+a2xz+a3y2+a4yz+a5z2=a1(x+a2z2a1)2+a3(y+a4z2a3)2+(a5a224a1a244a3)z2.

    In view of the above equation, (2.1) leads to (2.2).

    Now we will prove the key estimate for the proof of Theorem 1.2.

    Lemma 2.3. Let (u, v, w) be a solution to (1.1). Under the conditions (1.3)-(1.9) and (1.11), there exist δ1,δ2>0andε>0 such that the nonnegative functions E1 and F1 defined by

    E1(t):=Ω(u1logu)+δ1μ1μ2Ω(v1logv)+δ22Ω(w˜w)2

    and

    F1(t):=Ω(u1)2+Ω(v1)2+Ω(w˜w)2%+Ω|w|2

    satisfy

    ddtE1(t)εF1(t)(t>0). (2.3)

    Proof. Thanks to (1.11), we can choose δ1=βα>0andδ2>0 satisfying

    max{χ1(0)2(1+δ1)4d,μ1χ2(0)2(1+δ1)4μ2d}<δ2<4μ1γδ1α2δ1+β2. (2.4)

    We denote by A1(t), B1(t), C1(t) the functions defined as

    A1(t):=Ω(u1logu),B1(t)=Ω(v1logv),C1(t):=12Ω(w˜w)2,

    and we write as

    E1(t)=A1(t)+δ1μ1μ2B1(t)+δ2C1(t).

    The Taylor formula applied to H(s)=s-log s (s≥0) yields A1(t)=Ω(H(u)H(1)) is a nonnegative function for t > 0 (more detail, see [1, Lemma 3.2]). Similarly, we have that B1(t) is a positive function. By straightforward calculations we infer

    ddtA1(t)=μ1Ω(u1)2Ω|u|2u2+Ωχ1(w)uuw,ddtB1(t)=μ2Ω(v1)2Ω|v|2v2+Ωχ2(w)vvw,ddtC1(t)=Ωhu(u1)(w˜w)+Ωhv(v1)(w˜w)+Ωhw(w˜w)2dΩ|w|2

    with some derivatives hu, hv and hw. Hence we have

    ddtE1(t)=I1(t)+I2(t), (2.5)

    where

    I1(t):=μ1Ω(u1)2δ1μ1Ω(v1)2+δ2Ωhu(u1)(w˜w)+δ2Ωhv(v1)(w˜w)+δ2Ωhw(w˜w)2

    and

    I2(t):=Ω|u|2u2+Ωχ1(w)uuwδ1μ1μ2Ω|v|2v2+δ1μ1μ2Ωχ2(w)vvwdδ2Ω|w|2. (2.6)

    At first, we shall show from Lemma 2.2 that there exists "1 > 0 such that

    I1(t)ε1(Ω(u1)2+Ω(v1)2+Ω(w˜w)2). (2.7)

    To see this, we put

    g1(ε):=μ1ε,g2(ε):=δ1μ1ε,g3(ε):=(δ2hwε)h2u4(μ1ε)δ22h2v4(δ1μ1ε)δ22.

    Since µ1 > 0 and δ1=βα>0, we have g1(0)=µ1 > 0 and g2(0)=δ1μ1>0. In light of (1.5) and the definitions of δ2,α,β>0 (see (1.10) and (2.4)) we obtain

    g3(0)=δ2(hw(h2u4μ1+h2v4δ1μ1)δ2)δ2(γ(α2δ1+β4δ1μ1)δ2)>0.

    Combination of the above inequalities and the continuity of gi for i=1, 2, 3 yield that there exists ε1>0 such that gi(ε1) > 0 hold for i=1, 2, 3. Thanks to Lemma 2.2 with

    a1=μ1ε1,a2=δ2hu,a3=δ1μ1ε1,a4=δ2hv,a5=δ2hwε1,x=u(t)1,y=v(t)1,z=w(t)˜w,

    we obtain (2.7) with ε1>0. Lastly we will prove

    I2(t)0. (2.8)

    Noting that χi<0 (from (1.8)) and then using the Young inequality, we have

    Ωχ1(w)uuwχ1(0)Ω|uw|uχ1(0)2(1+δ1)4dδ2Ω|u|2u2+dδ21+δ1Ω|w|2

    and

    δ1μ1μ2Ωχ2(w)vvwχ2(0)δ1μ1μ2Ω|vw|vχ2(0)2δ1(1+δ1)4dδ2(μ1μ2)2Ω|v|2v2+dδ1δ21+δ1Ω|w|2.

    Plugging these into (2.6) we infer

    I2(t)(1χ1(0)2(1+δ1)4dδ2)Ω|u|2u2δ1μ1μ2(1μ1χ2(0)2(1+δ1)4dμ2δ2)Ω|v|2v2.

    We note from the definition of δ2>0 that

    1χ1(0)2(1+δ1)4dδ2>0,1μ1χ2(0)2(1+δ1)4dμ2δ2>0.

    Thus we have (2.8). Combination of (2.5), (2.7) and (2.8) implies the end of the proof.

    Lemma 2.4. Let (u, v, w) be a solution to (1.1). Under the conditions (1.3)-(1.9) and (1.11), (u, v, w) has the following asymptotic behavior:

    u(t)1L(Ω)0,v(t)1L(Ω)0,w(t)˜wL(Ω)0(t).

    Proof. Firstly the boundedness of u, v, w and a standard parabolic regularity theory ([9]) yield that there exist θ(0,1) and C > 0 such that

    uC2+θ,1+θ2(ˉΩ×[1,t])+vC2+θ,1+θ2(ˉΩ×[1,t])+wC2+θ,1+θ2(ˉΩ×[1,t])C for  all t1.

    Therefore in view of the Gagliardo-Nirenberg inequality

    φL(Ω)cφNN+2W1,(Ω)φ2N+2L(Ω)(φW1,(Ω)), (2.9)

    it is sufficient to show that

    u(t)1L2(Ω)0,v(t)1L2(Ω)0,w(t)˜wL2(Ω)0(t).

    We let

    f1(t):=Ω(u1)2+Ω(v1)2+Ω(w˜w)2.

    We have that f1(t) is a nonnegative function, and thanks to the regularity of u, v, w we can see that f1(t) is uniformly continuous. Moreover, integrating (2.3) over (1, ∞), we infer from the positivity of E1(t) that

    1f1(t)dt1εE1(1)<.

    Therefore we conclude from Lemma 2.1 that f1(t)→0 (t→∞), which means

    Ω(u1)2+Ω(v1)2+Ω(w˜w)20(t).

    This implies the end of the proof.

    Lemma 2.5. Let (u, v, w) be a solution to (1.1). Under the conditions (1.3)-(1.9) and (1.11), there exist C > 0 and λ>0 such that

    u(t)1L(Ω)+v(t)1L(Ω)+w(t)˜wL(Ω)Ceλt(t>0).

    Proof. From the L’Hôpital theorem applied to H(s) :=s-log s we can see

    lims1H(s)H(1)(s1)2=lims1H(s)2=12. (2.10)

    In view of the combination of (2.10) and u1L(Ω)0 from Lemma 2.4 we obtain that there exists t0 > 0 such that

    14Ω(u1)2A1(t)=Ω(H(u)H(1))Ω(u1)2(t>t0). (2.11)

    A similar argument, for the function v, yields that there exists t1 > t0 such that

    14Ω(v1)2B1(t)Ω(v1)2(t>t1). (2.12)

    We infer from (2.11) and the definitions of E1(t), F1(t) that

    E1(t)c6F1(t)

    for all t > t1 with some c6 > 0. Plugging this into (2.3), we have

    ddtE1(t)εF1(t)εc6E1(t)(t>t1),

    which implies that there exist c7 > 0 and >0 such that

    E1(t)c7et(t>t1).

    Thus we obtain from (2.11) and (2.12) that

    Ω(u1)2+Ω(v1)2+Ω(w˜w)2c8E1(t)c7c8et

    for all t > t1 with some c8 > 0. From the Gagliardo-Nirenberg inequality (2.9) with the regularity of u, v, w, we achieve that there exist C > 0 and λ>0 such that

    u(t)1L(Ω)+v(t)1L(Ω)+w(t)˜wL(Ω)Ceλt(t>0).

    This completes the proof of Lemma 2.5.

    Proof of Theorem 1.2. Theorem 1.2 follows directly from Lemma 2.5.


    Acknowledgments

    The authors would like to thank the referee for valuable comments improving the paper.


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