For testing the significance of regression coefficients, go ahead and log‐transform count data

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Violating the normality assumption may be the lesser of two evils (2018, methodology): “…that were severely skewed, platy- and leptokurtic or zero-inflated (distributions D0-D9; Figure 1A left column), going beyond previous studies that examined less dramatic violations (Bishara & Hittner 2012; Puth, Neuhauser & Ruxton 2014; Ives 2015; Szöcs & Schäfer 2015; Warton et al. 2016).”
Semi‐natural habitats mitigate the effects of temperature rise on wild bees (2017, methodology): “This circumvents problems with null hypothesis testing of complex GLMMs, such as inflated type I error (Ives 2015).”
A brief introduction to mixed effects modelling and multi-model inference in ecology (2018, methodology): “…the fact that there is unlikely to be a universally best approach; each method will have its own strengths and weakness depending on the (2010); Ives (2015) and Warton et al (2016) argue the relative merits of GLMs vs log-365 transformation of count data; Warton & Hui (2011) address the…”