# Photoacclimation strategies in Phaeodactylum tricornutum biofilms

Beatriz Felices-Rando, Andrea Fanesi, Eleonora Sforza, Fabrizio Bezzo, Filipa Lopes

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Beatriz Felices-Rando, Andrea Fanesi, Eleonora Sforza, Fabrizio Bezzo, Filipa Lopes. Photoacclimation strategies in Phaeodactylum tricornutum biofilms. Algal Research - Biomass, Biofuels and Bioproducts, 2025, 90, pp.104111. 10.1016/j.algal.2025.104111. hal-05096388

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1 **Photoacclimation strategies in *Phaeodactylum tricornutum* biofilms**

2 Beatriz Felices-Randoª, Andrea Fanesiᵇ*, Eleonora Sforzaª, Fabrizio Bezzoª, Filipa Lopesᵇ

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ªDepartment of Industrial Engineering, University of Padova, Via Marzolo 9, Padova 35131,
Italy

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ᵇCentraleSupélec, Laboratoire Génie des Procédés et Matériaux (LGPM), Université
Paris- Saclay, Gif-sur-Yvette, France

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*Corresponding author:

9 Dr. Andrea Fanesi

10 andrea.fanesi@centralesupelec.fr

11 Tel.: +33175316615

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## Abstract

Microalgal biofilms are a promising alternative to conventional suspended cultures, offering increased biomass densities with reduced water and energy demands for cultivation and harvesting. However, to fully demonstrate their interest for large-scale production, a better understanding of the impact of operational factors on biofilm structure is required. This study explores the effect of four different photon flux densities (75, 150, 300 and 600 µmol m⁻² s⁻¹) on *Phaeodactylum tricornutum* biofilms cultivated in a millifluidic system. For the first time, biofilm structure and physiology were characterised *in situ*, non-destructively by complementary imaging tools (Confocal Laser Scanning Microscopy, CLSM, and Optical Coherence Tomography, OCT) and dissolved oxygen measurements. Biofilms cultivated at 150 and 300 µmol m⁻² s⁻¹ presented the highest growth rates (0.31 and 0.38 d⁻¹) while higher light intensities (600 µmol m⁻² s⁻¹) induced photoinhibition. On the other hand, biofilms at 75 µmol m⁻² s⁻¹ exhibited the lowest growth rate (0.23 d⁻¹) but they were extremely efficient in converting absorbed light into biomass (2.5 times more efficient than the biofilms grown at 300 µmol m⁻² s⁻¹). Interestingly, adjustments in the optical properties of biofilms exposed to different light conditions were observed through changes in the light extinction coefficient with biofilms becoming more transparent when their thickness was higher than 200–300 µm. These findings reveal important photoacclimation strategies in *P. tricornutum* biofilms and highlight the potential of exploiting different light intensities and harvesting strategies to optimise the operation of biofilm-based processes.

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## Keywords

Photoacclimation, *Phaeodactylum tricornutum*, photosynthetic biofilms, light intensity, optical coherence tomography (OCT), microalgae cultivation

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## Highlights

* *Phaeodactylum tricornutum* grows efficiently in biofilms

* CLSM and OCT were combined for non-destructive, *in situ* biofilm characterisation

* Biofilms at 150 µmol m⁻² s⁻¹ showed the highest growth rate

* 75 µmol m⁻² s⁻¹ resulted in the greatest light-use efficiency

* Physiological acclimation to light included changes in biofilm transparency
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## 1. Introduction

In biofilm cultivation systems, microalgae grow attached to a surface rather than being suspended in liquid, producing highly dense biomass layers that make the harvesting process much simpler, reducing dewatering and energy costs [1]. Currently, microalgae biofilm systems are mainly used for wastewater treatment [2,3]. In such systems, biofilms play a key role in nutrient removal and biomass recovery. While wastewater treatment remains their primary application, there is a growing interest in using biofilm-based systems for the production of high-value compounds [4–6].

The operation of biofilm-based systems is still hindered by the limited knowledge regarding microalgae behaviour as a function of operational factors such as light or nutrient availability. In suspended cultures, cells are continuously mixed, which helps to distribute light and nutrients more evenly across the culture. In contrast, cells in biofilms are immobilised within a matrix of extracellular polymeric substance (EPS) and subjected to light and chemical (e.g. nutrients and gases) gradients. As a result, while cells near the surface of a biofilm are exposed to high light intensity, those in deeper layers experience low-light or even dark conditions. Similarly, oxygen gradients can strongly influence cell activity [6,7]. High oxygen concentrations can indeed activate photorespiration, due to a shift of RuBisCo from carboxylase to oxygenase and reducing the rate of photosynthesis [8,9]. In addition, excessive oxygen levels can promote the formation of reactive oxygen species (ROS), causing oxidative stress that damages cells [6]. While similar inhibitory mechanisms occur in suspended cultures, the effects of high dissolved oxygen concentrations in biofilms can be amplified by limited gas exchange and local oxygen accumulation within the matrix. Understanding how these gradients in light intensity and oxygen concentration affect biofilm growth and composition is essential for evaluating the feasibility of these systems on an industrial scale [10].

Among all the factors influencing algal growth, light is one of the most complex and considered critical for optimising microalgal cultivation [7–9]. To cope with changing light conditions, microalgae have evolved various metabolic strategies collectively known as photoacclimation. These physiological mechanisms include modifications of the photosynthetic apparatus, such as adjustments in chlorophyll content, activation of photoprotective mechanisms (non-photochemical quenching, NPQ), and upregulation of
photosynthetic enzymes to enhance their metabolic capacity under high excitation pressure. Overall, these strategies are essential for the cells to maintain a balance between light harvesting capacity and utilisation while preventing photodamage [10,11].

While the responses triggered by different light intensities in suspended cultures are very well characterised [12], the effect of light on monospecific microalgal biofilms is less studied. This is of particular interest from both a scientific and a practical point of view. Unlike in planktonic cultures, when growing in a biofilm, microalgae are exposed to a continuous flux of photons due to immobilization, possibly leading to unique acclimation strategies. For example, architectural changes (i.e. biofilm thickness, cell/EPS organisation, porosity, etc.) could also be interpreted as an additional acclimation mechanism (besides cell physiological adjustments) that may help to increase cells fitness under changing light conditions. Indeed, recent studies have shown that light intensity, quality and cycles (i.e. intermittent light) may strongly affect microalgae biofilm architecture [13], with high light (500 µmol photons m⁻² s⁻¹) stimulating aggregation patterns in *Chlorella vulgaris* [14] and white light increasing porosity and roughness with respect to red and blue lights in *Scenedesmus obliquus* biofilms [15]. These observations suggest that in immobilised populations, architectural features can change strongly with light, helping to alter the local environment to which the cells are exposed. However, more research is need at this regard. From a commercial perspective, a better comprehension of biofilm architecture behaviour as a function of light and the identification of an optimal photon flux density (PFD) that maximises growth while maintaining affordable energetic expenses could also be a clear advantage in terms of economic feasibility of a given biofilm-based bioprocess.

In order to simulate realistic environmental conditions at lab-scale, continuous millifluidic, microfluidic and nanofluidic technologies have emerged in the past years as valuable tools for interdisciplinary studies involving physics, biology and engineering.

These technologies enable high-throughput studies for rapid data generation, allowing for precise control and monitoring of environmental factors [16–20]. The coupling of this type of systems with non-destructive imaging techniques such as confocal laser scanning microscopy (CLSM) and optical coherence tomography (OCT) allows to study *in situ* the impact of environmental variables such as light intensity on biofilm dynamics. CLSM enables the acquisition of high-resolution images of biofilms at the microscale (10 to 100 µm) in a non-invasive, non-destructive way [21,22]. However, one limitation of CLSM arises when analysing thick samples that limit the penetration
162 depth of the laser beam, hindering CLSM ability to capture the whole biofilm structure
163 Optical coherence tomography, on the other hand, presents greater penetration
164 depth and allows for *in situ* monitoring of structures at the mesoscale (several mm)
165 without the need of staining agents [24].

166 In this work, an original millifluidic setup was used to monitor the impact of light
167 intensity on biofilms of *Phaeodactylum tricornutum*, a diatom widely recognised for its
168 potential to remove pollutants from wastewater [25,26] and known to accumulate high-
169 value compounds such as EPA or fucoxanthin [27], with additional potential for
170 biomedical applications [28]. Architectural dynamics and oxygen production were
171 characterised, *in situ* and non-destructively, by multimodal imaging (CLSM and OCT)
172 to cover the full range of spatial scales and assess metabolic activity.

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## 2. Materials and methods

175 **2.1. Planktonic cultures**

176 *Phaeodactylum tricornutum* CCAP 1055/1 (CCAP, Culture collection of Algae and
177 Protozoa, Oban) was cultivated in F/2 medium [29] in borosilicate culture tubes at 23°C
178 and four irradiance levels (75, 150, 300 and 600 µmol m⁻² s⁻¹) to acclimate the
179 planktonic cultures prior to inoculation for biofilm growth. The cultures were bubbled
180 with filtered air and maintained within a cell concentration range of 10⁵ to 10⁷ cell mL⁻¹.

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182 **2.2. Biofilm cultivation: inoculum, adhesion and dynamics**

183 *P. tricornutum* biofilms were cultivated in flow-cells made of polymethyl methacrylate
184 (PMMA) covered with a 0.17 mm-thick glass coverslip. The volume capacity of the
185 flow-cells was 1.2 mL (40 × 10 × 3 mm). The experimental setup consisted of a
186 recirculation system where the culture medium (F/2) was fed by a peristaltic pump into
187 the sterilised flow-cells at a flowrate of 1 mL min⁻¹ and recycled back from the outlet
188 into the bottle. Under these conditions, the flow regime was characterized by a
189 Reynolds number of 7.4, indicating laminar flow. A bubble trap was located at the inlet
190 of the flow-cells to remove air bubbles that could damage the biofilms. A flow-through
191 oxygen optical sensor (FTC-PSt3; PreSens Precision Sensing GmbH, Germany) was
192 placed at the inlet and outlet of the flow-cells, which enabled online dissolved oxygen
193 (DO) measurements for a daily quantification of biofilm photosynthetic activity. A
194 schematic representation of the system is reported in Figure 1.
Before each experiment, the system was sterilised by circulating a commercial bleach solution (0.5% v/v) for 2 hours, then rinsed with 2 L of sterile milli-Q water and finally filled with growth medium. To prevent photosynthetic growth in the recycled medium, the bottles were covered with aluminium foil, creating dark conditions. The medium in the bottles was not mixed, and the feeding tubes were submerged only in the upper half of the liquid to prevent settled cells from being fed back into the system.

The flow-cells were inoculated with a 4 mL solution containing 2·10⁶ cell mL⁻¹ from the planktonic cultures acclimated to the irradiance under study. After inoculation, the cells were left overnight to settle and promote adhesion. From the next morning, the culture medium was continuously supplied to the flow-cells for over 11 days. Four light intensities were tested: 75, 150, 300 and 600 µmol m⁻² s⁻¹. Each experiment was repeated at least 2 times to ensure the replicability of the results. All the experiments were performed at 23°C.

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## 2.3. Light attenuation

Back irradiance (BI, µmol m⁻² s⁻¹) was measured daily with a quantum sensor (LI-190R; LI-COR Biosciences GmbH) at the bottom of the flow-cells. These measurements were used to calculate the light attenuated by the biofilms, according to:

$$ \text{Light attenuated (\%)} = \left( 1 - \frac{BI}{BI_0} \right) \cdot 100 \qquad (1) $$
where $BI_0$ (µmol m⁻² s⁻¹) is the back irradiance measured on day 0.

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## 2.4. Microscale and mesoscale imaging of biofilms: CLSM and OCT measurements

Every flow-cell was scanned daily with an inverted Zeiss LSM700 confocal laser scanning microscope (CLSM, Carl Zeiss Microscopy GmbH, Jena, Germany). The CLSM was controlled by the Zen 10.0 software black edition (Carl Zeiss Microscopy GmbH, Jena, Germany). Biofilms were scanned using a LD Plan-Neofluar 20x0.4 Karr M27 objective with a 0.4 N.A. (numerical aperture). Each image (512 × 512 pixels) was 640.17 × 640.17 µm in size, and the z-step applied for obtaining the z-stacks of the biofilms was 3.94 µm. Every day, each flow cell was scanned always at the same exact five positions (by previous calibration of the xy-motorised stage), from the inlet to the outlet, along the length of the flow-cell. The cells were detected by exciting chlorophyll

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a at 639 nm and detecting chlorophyll a autofluorescence with a long pass filter of 227 228 615 nm [30].

A spectral-domain optical coherence tomograph (OCT, Ganymede 621, Thorlabs GmbH) with a central light source of 900 nm wavelength was used to capture the meso- 229 230 structure of the biofilms. The images were acquired using a telecentric scan lens (OCT- 231 232 LK3-BB) at a speed of 25 kHz per A-scan, averaging six A-scans per measurement. The 233 field of view was 9 × 9 mm (XY) and the axial depth 1 mm (Z). The lateral pixel 234 resolution was 18.07 µm and the axial pixel resolution was 1.45 µm. For all the 235 acquisitions, a refractive index of 1.33 was used as the biofilms were imaged in situ in a 236 liquid medium [31]. Image acquisitions by OCT were managed by the software 237 ThorImageOCT 5.4.4 (Thorlabs). Four OCT scans of each flow-cell were needed to 238 capture the totality of the biofilms (i.e. 4 cm).

A custom script [32] running in FIJI [33] was used to extract quantitative parameters 239 (biovolume and mean biofilm thickness) from the images acquired with both imaging 240 techniques. Parameters were calculated according to the computation described in 241 COMSTAT 2.1 (Technical University of Denmark [34]) and according to Wagner et al. 242 [31]. The detailed equations are included in the Supporting Information (Eq. S1 and 243 S2). 244

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## 2.5. Optical properties of the biofilms: light extinction coefficient

The variation of the light extinction coefficient ($k_a$, µm⁻¹) over time was calculated at 247 every light intensity using the Lambert-Beer law, which describes light attenuation in 248 biofilms following the expression [35]: 249

$$I_{\text{out}} = I_{\text{in}} \cdot e^{-k_a X} \qquad (2)$$

where $I_{in}$ (µmol m⁻² s⁻¹) is the incident light irradiance, $I_{out}$ (µmol m⁻² s⁻¹) is the 250 measured back irradiance, and $X$ (µm) represents biofilm thickness, obtained from OCT 251 measurements. 252

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## 2.6. Biofilm chemical composition

Chl a was extracted from the cells using acetone (90% v/v). Chl a content was 255 quantified by measuring the absorption at 630, 649, 664 and 665 nm with an Evolution 256 60S UV-visible spectrophotometer (Thermo Scientific, Madison, WI, USA). Chl a 257 concentration was calculated according to [36]: 258
$$ Chl a (\mu g mL^{-1}) = 11.47 \times OD_{664} - 0.40 \times OD_{630} \quad (3) $$

## 2.7. Dissolved oxygen concentration

DO (mg L⁻¹) was measured at the inlet and outlet of the flow-cells with a flow-through oxygen optical sensor (FTC-PSt3; PreSens Precision Sensing GmbH, Germany). To calibrate the oxygen sensor, a 0% oxygen solution was prepared by dissolving 1 g of Na₂SO₃ in 100 mL of distilled water. For the 100% oxygen saturated solution, distilled water was bubbled with air for at least 15 minutes. The sensor was first immersed in the deoxygenated solution to set the 0% calibration, then in the oxygen-saturated water to set the 100% calibration.

## 2.8. Growth rate estimates

### Growth rate from light transmittance

The specific growth rate (μᵢ, d⁻¹) based on light transmittance was determined from back irradiance measurements from day 1 to day 7 (exponential growth phase), using the slope of the regression between ln(ln(lin/lout)) and time (t, d). This approach combines the expression X = X₀eμt with the Lambert-Beer law—Eq. (2) [14]—, with X and X₀ representing biofilm thickness at times 0 and t, respectively.

### Growth rate from biovolume: linear regression

Microbial growth is generally defined by the following expression [37]:

$$ N(t) = N_0 e^{\mu t} \quad (4) $$

where N(t) represents the number of cells at time t, N₀ is the initial number of cells, and μ represents the specific growth rate (h⁻¹) of the culture. Assuming that the biovolume measured by OCT imaging is proportional to N(t), the following expression derived from Eq. (4) can be used to calculate μ from OCT measurements by performing a linear regression on the natural logarithm of biovolume versus time:

$$ \ln(X_t^{BV}) = \ln(X_0^{BV}) + \mu t \quad (5) $$

where X_t BV (μm³ μm⁻²) is the biovolume obtained from OCT imaging at time t, and X_0 BV (μm³ μm⁻²) is the initial biovolume. This method assumes a constant, exponential growth pattern over the measurement period (from day 1 to 9).

## 2.9. Productivity
Biomass productivities ($P_x$, µm³ µm⁻² day⁻¹) were calculated at each light intensity with the following formula, using biovolume data from days 1–11 obtained from OCT measurements and time steps (Δtime) of 1 day:

$$P_x = \frac{\Delta \text{Biovolume}}{\Delta \text{time}} \qquad (6)$$

The $P_x$ values obtained (days 1–11) were then used to calculate biomass productivity per photons absorbed ($P_x^{abs}$, µm³ µmol photon⁻¹):

$$P_x^{abs} = \frac{P_x}{I_{in} - I_{out}} \qquad (7)$$

where $I_{in}$ (µmol m⁻² s⁻¹) is the incident light intensity, and $I_{out}$ (µmol m⁻² s⁻¹) is the back irradiance.

Productivity of biomass per incident photons ($P_x^{in}$, µm³ µmol photon⁻¹) was also calculated for days 1–11, according to:

$$P_x^{in} = \frac{P_x}{I_{in}} \qquad (8)$$

## 2.10. Statistical analysis

All experiments were performed on at least two biological replicates. To assess the effect of light intensity on chlorophyll content, biomass productivities and growth rates, and to evaluate whether different regression methods make a significant difference, one-way and two-way analysis of variance (ANOVA) were conducted using SciPy and StatsModels in Python [38,39]. Following that, a Tukey's post-hoc test was carried out for pairwise comparisons. The results were interpreted using a significance threshold of $\alpha = 0.05$.

# 3. Results

## 3.1. Impact of light irradiance on biofilm growth dynamics

CLSM and OCT images of biofilms cultivated under 75, 150 and 300 µmol m⁻² s⁻¹ are presented in Figures 2, S1 and S2, while the temporal dynamics of biovolume and average thickness are depicted in Figure 3 and S3. Biofilms exposed to 600 µmol m⁻² s⁻¹ showed no visible growth, suggesting strong photoinhibition. At this irradiance, no cells were indeed detected by CLSM, likely due to pigment bleaching caused by excessive light exposure. Consequently, the study focuses mainly on biofilms grown under the three lower light intensities.
Significant differences are observed in the patterns of the structural parameters obtained by CLSM (Fig S3) and OCT (Fig 3). This discrepancy is certainly due to technological limitations of CLSM imaging: laser penetration is hindered in thick and/or compact biofilms, as those of the present study, which reached up to 600 µm in thickness, as previously described [40,41].

It also appears that biofilm morphology is affected by light intensity, as confirmed by our previous work with *C. vulgaris* biofilms [35]. While cells exposed to high light (150 and 300 µmol m⁻² s⁻¹) form clusters during the first stage of biofilm development (up to day 4), those at 75 µmol m⁻² s⁻¹ grow by spreading over the entire substrate (Figure S2). Interestingly, biofilms grown at 300 µmol m⁻² s⁻¹ also have a more compact structure than those grown at lower light intensities.

The dynamics of attenuated light and structural features (data retrieved from OCT imaging) for biofilms formed at different light regimes are shown in Fig. 3. Light attenuates (Fig. 3C) with biofilm development, regardless of the light regime, which is consistent with an increase in biovolume and biofilm thickness (Figure 3A, 3B). It is also noticeable that the biofilms cultivated under an irradiance of 600 µmol m⁻² s⁻¹ exhibited no growth. Additionally, no significant differences in light attenuation are detected for biofilms grown under 150 and 300 µmol m⁻² s⁻¹. In contrast, biofilms at 75 µmol m⁻² s⁻¹ consistently show significantly lower PFD attenuation levels (*P* = 0.03 and *P* = 0.04), with this difference becoming more pronounced in the later stages of biofilm maturation (a 40% of light is attenuated on day 11, against the 80% of attenuation observed at 150 µmol m⁻² s⁻¹ and 300 µmol m⁻² s⁻¹). Interestingly, the amount of light absorbed reaches a limit at a certain thickness for biofilms cultivated at 75 µmol m⁻² s⁻¹ and 150 µmol m⁻² s⁻¹, while it continues to increase at 300 µmol m⁻² s⁻¹ (Fig. 3D). Beyond 400 µm (or 200 µm in the case of biofilms cultivated at 75 µmol m⁻² s⁻¹), light attenuation presents a slower (or null) increase with biofilm thicknesses.

Specific growth rates obtained from data of light transmittance and biovolume (OCT) are reported in Table 1. Accordingly, biofilms at 150 µmol m⁻² s⁻¹ presented the highest growth rate, regardless of the estimation method used (*P* < 0.004).
<table><caption>**Table 1.** Values of growth rate obtained from the regression of the natural logarithm of biovolume versus time at each light intensity, using measurements obtained from OCT ($\mu_{OCT}$), and growth rates obtained from back irradiance measurements ($\mu_{light}$).</caption><thead><tr><th><b>I</b><br>(µmol m<sup>-2</sup> s<sup>-1</sup>)</th><th><i>μ</i><sub>OCT</sub><sup>*</sup><br>(d<sup>-1</sup>)</th><th><i>μ</i><sub>light</sub><sup>†</sup><br>(d<sup>-1</sup>)</th></tr></thead><tbody><tr><td><b>75</b></td><td>0.23 ± 0.02<sup>a</sup></td><td>0.27 ± 0.01<sup>a</sup></td></tr><tr><td><b>150</b></td><td>0.31 ± 0.02<sup>b</sup></td><td>0.57 ± 0.03<sup>b</sup></td></tr><tr><td><b>300</b></td><td>0.28 ± 0.02<sup>c</sup></td><td>0.48 ± 0.04<sup>c</sup></td></tr></tbody></table>

Different letters represent statistically different means (P < 0.05).

## 3.2. Optical properties of the biofilms

Figure 4A shows the evolution of the light extinction coefficient $k_a$ over time. A steady increase of $k_a$ is observed until day 7 at all light intensities, corresponding to thicknesses of about 300 µm (or 150 µm in the case of biofilms cultivated at 75 µmol m⁻² s⁻¹). It is particularly interesting to notice the sudden drop of this coefficient at 75 µmol m⁻² s⁻¹ beyond thicknesses of 200 µm (Figure 4B).

## 3.3. Oxygen measurements

Figure 5 shows the net oxygen production against biovolume for biofilms grown at 75 µmol m⁻² s⁻¹ and 150 µmol m⁻² s⁻¹. Interestingly, different patterns can be observed: while a linear relationship is observed for biofilms at 150 µmol m⁻² s⁻¹, a decrease in oxygen generation is detected for thickness higher than 100 µm in case of those developed at 75 µmol m⁻² s⁻¹.

## 3.4. Productivities

Biomass productivities ($P_x$, µm³ µm⁻² day⁻¹ and $P_x^{abs}$, µm³ µmol photon⁻¹) are presented in Fig 6A and B, while data of $P_x^{in}$ (µm³ µmol photon⁻¹) are represented in Figure S4. Biofilms cultivated at 75 µmol m⁻² s⁻¹ presented the greatest efficiency in converting photons into biomass (Figure 6B). In contrast, biofilms cultivated at 150 and 300 µmol m⁻² s⁻¹ presented the highest daily productivity but exhibited a lower photon conversion efficiency compared to the biofilms cultivated at 75 µmol m⁻² s⁻¹.

<footnote>* Using data from days 1–9 for the calculation.</footnote>

<footnote>† Using data from days 1–7 for the calculation.</footnote>
376 **4. Discussion**

377 Diatoms thrive in environments where light conditions change over short time scales, ranging from seconds to minutes. Consequently, they have evolved efficient acclimation strategies to optimise light usage and avoid photodamage [42]. The available literature about planktonic and benthic diatom responses to light is exhaustive, both in terms of growth performance and physiological adjustments. Multiple studies have been conducted in suspended or immobilised (and mostly mixed) communities [11,43–47].

383 Conversely, only very few studies have investigated the structural changes or growth dynamics of monospecific diatom biofilms under controlled environmental conditions [30,48]. Nevertheless, with the rise of biofilm-based technologies in industry, filling this knowledge gap becomes essential for optimising diatom bioprocess technologies.

387 When considering benthic diatoms, their acclimation strategies to low/high light not only involve physiological adjustments but also include higher level mechanisms such as vertical migrations in sediments and changes in cell orientation. Similarly, the 3D structure of biofilms (i.e., spatial organisation of cells and EPS) could induce peculiar adjustments, allowing sessile cells to cope with changes in light availability. To test this hypothesis, a milli-fluidic approach was used to cultivate and characterise *P. tricornutum* biofilms in terms of architecture and optical properties as a function of different photon flux densities. Biofilms were visualized *in situ* at different scales thanks to a multimodal imaging approach (CLSM and OCT).

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Our results demonstrate that high-resolution CLSM imaging can be used to characterize the early stages of biofilm development (biofilms with thicknesses well below 100 µm), while OCT provides structural information on mature biofilms over larger areas. Similar conclusions have been drawn in other studies on bacterial biofilms [31,49].

In planktonic mode, *P. tricornutum* growth has been reported to be light limited at 30 µmol m⁻² s⁻¹ and saturated at 300 µmol m⁻² s⁻¹, while no further increase in growth is observed at higher intensities, at which photoprotective mechanisms are activated [50–52]. Here, we report for the first time similar growth patterns in *P. tricornutum* biofilms as a function of light: photolimitation is observed at 75 µmol m⁻² s⁻¹, as demonstrated by the lowest growth rate and final biomass, while photoinhibition occurs at 600 µmol m⁻² s⁻¹.

In addition, the fact that biofilms grown at 75 and 150 µmol m⁻² s⁻¹ reached a plateau (Fig. 3) suggests the presence of a limiting mechanism. Light and nutrients (including
CO₂) are the typical limiting resources for photosynthetic cells. The transmitted light at 75 and 150 µmol m⁻² s⁻¹ on day 11 was 45 and 33 µmol m⁻² s⁻¹, respectively. These values are far from the compensation point (*I*<sub>c</sub>, which represents the light intensity at which the rate of photosynthesis equals the rate of respiration) reported by Geider et al. [46], who derived an *I*<sub>c</sub> value of less than 1 µmol m⁻² s⁻¹ for *P. tricornutum*. However, that compensation point was determined in planktonic cultures acclimated to very low light intensities (<10 µmol m⁻² s⁻¹), and the value of *I*<sub>c</sub> is known to depend on the irradiance of acclimation [47]. It should also be emphasised that the light attenuation measurements taken for the biofilms in this study are averaged across the bottom of the biofilm, and the actual scenario might likely include uneven structures and denser clusters of cells that may create microenvironments where light levels are much lower. Interestingly, the fact that biofilms continued to grow at 300 µmol m⁻² s⁻¹ (and had the highest biomass of the three light intensities) also suggests that nutrients were still sufficient to promote cell growth. Growth at 75 µmol m⁻² s⁻¹ is therefore unlikely to be nutrient limited. Besides photolimitation, it is also possible that O₂ produced by photosynthesis accumulated to an excessive extent under these conditions, inhibiting the carboxylase activity of RuBisCo and leading to increased photorespiration. Inhibition by oxygen was already proposed in the work of Polizzi et al. [53], who developed a spatial model to describe the growth dynamics of photosynthetic biofilms, considering the effects of light and oxygen, among other factors. Excessive concentrations of dissolved oxygen (beyond 20 mg L⁻¹) can induce ROS generation, leading to the destruction of the chloroplast structure [54–56].

The changes in biofilm architecture over time were accompanied by notable adjustments in their optical properties as a function of light intensity. Interestingly, the light extinction coefficient increased steadily at all the irradiances until day 7, after which it either stabilised (for biofilms at 150 and 300 µmol m⁻² s⁻¹) or declined sharply (as observed at 75 µmol m⁻² s⁻¹). This pattern reflects changes in biofilm composition, particularly in pigment content, probably aimed at improving light transmittance within the biofilm. These observations are further supported by the chl *a* content measured on day 11, with biofilms grown at 150 and 300 µmol m⁻² s⁻¹ showing significantly higher chl *a* levels than those at 75 µmol m⁻² s⁻¹ (Figure S5). This behaviour has been already proposed by other researchers. Indeed, the light field perceived by planktonic and immobilised cells can be quite different. Unlike planktonic cells grown in dense cultures, which are constantly exposed to oscillations in the light environment that
reduce the excitation pressure on the photosynthetic apparatus (even at high irradiances), microalgae in biofilms are exposed to a continuous flux of photons. This can lead to an atypical, inversed acclimation in microalgae biofilms where the increase in biomass density is followed by a decrease in pigment content [57]. For example, Gao et al. [35] measured cell volume and chlorophyll a content in *Chlorella vulgaris* biofilms, cultivated under different light irradiances in flow-cells and their results show a consistent decrease in both cell size and chl a content as the biofilms mature. Other authors have suggested that the decrease in pigment content guarantees light penetration into the deepest layers [58,59]. This coordinated behaviour may be regulated by quorum sensing mechanisms, where cell-to-cell communication enables the community to respond collectively to local environmental changes, optimising the distribution of resources and sustaining the biofilm's overall functioning and survival [32,60,61]. However, the specific role of quorum sensing in photosynthetic biofilm regulation remains largely unknown. This opens the way to future studies to confirm the hypothesized mechanism and further identifying the signalling molecules involved.

Interestingly, this physiological adjustment appeared to allow the cells in the biofilms grown at 150 µmol m⁻² s⁻¹ to remain photosynthetically active throughout their entire thickness with a steady increase in oxygen production over the whole growth period (Figure 5). On the contrary, the sudden decline in oxygen production observed in biofilms cultivated at 75 µmol m⁻² s⁻¹ might suggest that those cells, though more transparent to light, are reaching their compensation point. Indeed, the shift in the oxygen production trend at 75 µmol m⁻² s⁻¹ matches the point at which the light extinction coefficient starts to decrease (Figure 4). This might be explained by the fact that, as the biofilm grows, lower layers may become light-limited due to self-shading, and bottom cells may fall below *I*<sub>c</sub>. Below this point, the available light is insufficient to drive photosynthesis. Another possible explanation for the sudden decay in oxygen production and reduced chlorophyll a content at 75 µmol m⁻² s⁻¹ (see Figure S5 of Supporting Information) could be an excessive oxygen accumulation, leading to the formation of ROS and degradation of chlorophyll a.

From an industrial perspective, to fully exploit biofilm cultivation systems for industrial production, performance key factors like productivity per absorbed photons and per incident photons must be considered. According to our data, light was more efficiently used by biofilms grown at 75 µmol m⁻² s⁻¹ (higher productivity per absorbed photons; Figure 6B). This may be explained by the ability of cells to photoacclimate and
477 upregulate alternative ATP generation pathways, such as light-dependent respiration
478 and cyclic PSI electron transport, enhancing the efficiency of light utilisation [62,63].

479 Indeed, diatoms are well-known for their exceptional growth efficiency at low light
480 intensities [64]. On the other hand, although the highest growth rate and overall
481 productivity were found for 150 and 300 µmol m⁻² s⁻¹, productivity per unit of incident
482 light appeared to be light-independent (Figure S4).

483 Overall, these findings may help identifying optimal strategies to run a biofilm-based
484 system according to the target product. For example, the use of super-saturating light
485 intensities—combined with the use of ammonium as a nitrogen source—can increase
486 lipid biosynthesis in *P. tricornutum*, as reported by Huete-Ortega [65]. In contrast,
487 lower light irradiances appear to increase the accumulation of pigments like
488 fucoxanthin, according to Conceição et al. [52]. Regarding the use of *P. tricornutum* for
489 wastewater treatment applications, nutrient removal efficiency could potentially be
490 enhanced by optimising light conditions. Moreover, the ability of *P. tricornutum* to
491 efficiently utilise light at low irradiance levels may offer practical advantages for
492 outdoor systems or settings where light availability is limited.

493 With respect to biomass harvesting, identifying the threshold thickness beyond which
494 productivity begins to decline would ensure that resources are not wasted on
495 maintaining inactive layers. Additionally, a dynamic system that starts at low
496 irradiances and shifts to higher intensities as the biofilm grows could be useful to
497 optimise light efficiency across the biofilm growth cycle. In this context, real-time
498 monitoring of biofilm thickness using OCT shows strong potential for enabling dynamic
499 regulation of incident irradiance during cultivation. By coupling OCT data with
500 programmable lighting systems, it may become possible to dynamically adjust light
501 irradiance, helping to avoid photodamage during early biofilm development and
502 maximising overall productivity.

503 This study also opens several research questions that require further investigation. For
504 example, the potential oxygen accumulation in biofilms, which remains poorly studied,
505 could be verified through microprofiling techniques [66–68]. Regarding the scaling-up
506 of biofilm-based systems, specific challenges such as thickness control, nutrient
507 delivery or light management may be addressed through advanced modelling and
508 optimisation strategies, allowing a better prediction and regulation of the system
509 performance. Other issues such as contamination by unwanted microorganisms,
510 mechanical stability related to substrate materials, or evaporation losses affected by
temperature fluctuations will require dedicated engineering solutions and further experimental research [69].

513

## 5. Conclusions

In this study, a millifluidic platform was used for the first time to evaluate the effect of light intensity on *P. tricornutum* biofilms. CLSM and OCT were combined to characterise biofilm development at both micro and meso-scales. Our results clearly demonstrate the critical role of light intensity in shaping biofilm growth dynamics and morphology, with biofilms grown at the highest irradiance presenting a more compact structure. The changes in biofilm architecture over time were accompanied by notable adjustments in their optical properties as a function of light intensity, revealing important photoacclimation strategies in *P. tricornutum*.

Biofilms grown at 150 µmol m⁻² s⁻¹ showed the highest biomass productivity up to a threshold thickness (around 600 µm), while those grown at 75 µmol m⁻² s⁻¹ used light more efficiently but achieved the lowest overall biomass productivity due to light limitation and/or oxygen accumulation.

These results provide valuable insights for process design, highlighting the need to combine different light intensities and harvesting strategies to optimise productivity according to specific objectives.

530

**Funding:** This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 955520 DigitAlgaesation.

**Conflicts of Interest:** The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

**Acknowledgments:** The authors would like to thank the program Horizon 2020 for fundings, and the ANR (French National Research Agency) Alligator, PhotobiofilmExplorer and MoBioSens for sustaining their research.

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